Abstract: A teachable object contour mapping method for region partition receives an object boundary and a teaching image. An object contour mapping recipe creation is performed using the object boundary and the teaching image to generate object contour mapping recipe output. An object contour mapping is applied to an application image using the object contour mapping recipe and the application image to generate object contour map output. An object region partition using the object contour map to generate object region partition output. An updateable object contour mapping method receives a contour mapping recipe and a validation image. An object contour mapping is performed using the object contour mapping recipe and the validation image to generate validation contour map output. An object region partition receives a region mask to generate validation object region partition output. A boundary correction is performed using the validation object region partition to generate corrected object boundary output.

Abstract: An apparatus may include a memory, a processor circuit, and a connected component labeling module. The connected component labeling module may be operative of the processor circuit to determine one or more connected components during reading of an image comprising a multiplicity of pixels from the memory, assign a label to a plurality of pixels of the multiplicity of pixels, generate one or more label connections for a respective one or more labels, each label connection linking a higher label to a lowest label for the same connected component, and write to the memory for each label of the one or more labels a lowest label as defined by the label connection for the each label after a label is assigned to each pixel.

Abstract: A multi-point image labeling method adopts an image labeling device to label an object pixel matrix containing image data and makes adjacent array elements with image data have an identical image label value. Next, the image labeling device provides a multi-point label window, which designates a non-zero temporary labeled value to store in the register according to the temporary labeled value of the adjacent array elements. Next, the image labeling device provides a label-equivalence window, which generates label-equivalence information according to the adjacent temporary labeled values. Next, an equivalent-substitution processing process is performed on the temporary labeled values according to the label-equivalence information to generate label-equivalence substitution information. Then, the temporary labeled values are replaced according to the label-equivalence substitution information to obtain the resultant image labeled values and complete the image labeling of the object pixel matrix.

Abstract: A method and an apparatus for multi-label segmentation of an image are described. In a first step user defined labels are determined for one or more pixels of the image. Then a fraction of the pixels of the image for which no user defined label is determined is pre-initialized. Finally, a cellular automaton-based segmentation of the image is performed using the user defined labels and the pre-initialized pixels.

Abstract: A system for providing an adjusted image of a scene includes an optical assembly, a capturing system coupled to the optical assembly, and a control system. The optical assembly is adjustable to alternatively be focused on a first focal area and a second focal area that is different than the first focal area. The capturing system captures a first frame of the scene when the optical assembly is focused at the first focal area, and a second frame of the scene when the optical assembly is focused at the second focal area. The first frame includes a plurality of first pixels and the second frame includes a plurality of second pixels. The control system analyzes the first frame and the second frame and utilizes graph cuts techniques to assign a depth label to at least a portion of the first frame.

Abstract: A method and an apparatus for multi-label segmentation of an image are described. First an energy function is determined for the image. Then for a homogeneous region of the image variables of the energy function are grouped to a single variable. Subsequently the energy function is minimized and labels are assigned to regions of the image based on the minimized energy function.

Abstract: The present disclosure relates to systems and methods for classifying videos based on video content. For a given video file including a plurality of frames, a subset of frames is extracted for processing. Frames that are too dark, blurry, or otherwise poor classification candidates are discarded from the subset. Generally, material classification scores that describe type of material content likely included in each frame are calculated for the remaining frames in the subset. The material classification scores are used to generate material arrangement vectors that represent the spatial arrangement of material content in each frame. The material arrangement vectors are subsequently classified to generate a scene classification score vector for each frame. The scene classification results are averaged (or otherwise processed) across all frames in the subset to associate the video file with one or more predefined scene categories related to overall types of scene content of the video file.

Abstract: A method for identifying tooth regions. The method includes generating a first threshold image from a first tooth image by selecting intensity data values higher than a first predetermined threshold value c1; generating a second threshold image from a second tooth image by selecting intensity data values higher than a second predetermined threshold value c2; generating a preliminary tooth regions image that defines at least a first tooth region from the intersection of the first and second threshold images; generating a reference binary image from the first image by selecting intensity data values higher than a third predetermined threshold value c3, wherein threshold value c3 exceeds c1; and generating a refined tooth regions image from at least the first tooth region in the preliminary tooth regions image. The first tooth region is connected to objects in the reference binary image.

Abstract: Printer devices occasionally cause electronic documents to be automatically contracted prior to printing, in order to ensure that all of the content to be printed will fit within the dimensions of a page. Where the electronic document includes information having close tolerances, such as information to be printed on an address label or other defined region on a sheet, the automatic contraction may cause the information to be misaligned with respect to the label or other defined region. Automatically expanding the information within the electronic document prior to printing may counter this effect, and increase the likelihood that the information will be printed within the label or other defined region for which it is intended.

Abstract: An image to be shared with other users based on input from a first user is received. A second user is identified from a tag of the image, and information is provided, based at least in part on the tag, to one or both of the first user and the second user. Additionally, after editing of an image a determination can be made as to whether a region of the image having an associated tag has been affected by the editing. The tag associated with the region is altered if the region has been affected by the editing, otherwise the tag associated with the region is left unaltered. Furthermore, the tag can include a first portion storing data identifying a region of the image to which the tag corresponds, and a second portion storing data identifying a person shown in the region.

Abstract: An embodiment of the invention provides a method for sharing digital images on an image-sharing application, wherein a digital image is received from a user, the digital image including a first access setting defined by the user. A user-defined select region is identified on the digital image with a processor, wherein the select region includes a second access setting. Access to the digital image is permitted with an access controller based on the first access setting; and, access to the select region is permitted with the access controller based on the second access setting. In at least one embodiment, the digital image is displayed only to a first group of individuals based on the first access setting; and, the select region is displayed only to a second group of individuals based on the second access setting.

Abstract: An image processing method includes, calculating a partial distance between a pixel of interest in an image and each of reference pixels, sequentially calculating a total distance between the pixel of interest and each of the plurality of the reference pixels based on the partial distance, determining a shortest total distance among the total distances that have been already calculated, in the sequential calculation of the total distance, and categorizing the pixel of interest based on the reference pixel corresponding to the shortest total distance, wherein, if the partial distance between the pixel of interest and a specific one of the reference pixels to be calculated is equal to or greater than the shortest total distance in the sequential calculation of the total distance, the calculation of the total distance between the pixel of interest and the specific one of the reference pixels to be calculated is omitted.

Abstract: An embodiment of the invention provides a method for sharing digital images on an image-sharing application, wherein a digital image is received from a user, the digital image including a first access setting defined by the user. A user-defined select region is identified on the digital image with a processor, wherein the select region includes a second access setting. Access to the digital image is permitted with an access controller based on the first access setting; and, access to the select region is permitted with the access controller based on the second access setting. In at least one embodiment, the digital image is displayed only to a first group of individuals based on the first access setting; and, the select region is displayed only to a second group of individuals based on the second access setting.

Abstract: Systems and methods for image segmentation using a deformable atlas are provided. One method includes obtaining one or more target images, obtaining one or more propagated label probabilities for the one or more target images, and segmenting the one or more target images using a cost function of a deformable atlas model. The method further includes identifying segmented structures within the one or more target images based on the segmented one or more target images.

Abstract: The present invention is an image processing apparatus having: an acquisition unit configured to acquire a plurality of divided images; an extraction unit configured to extract a candidate region of a specific region in each of the plurality of images; a combining unit configured, in a case where candidate regions neighbor one another at the boundary in the plurality of images, to combine shape information of the plurality of neighboring candidate regions; and a determination unit configured to determine whether or not the plurality of candidate regions is a specific region by using the shape information combined by the combining unit.

Abstract: An improved branch-and-bound process of interval arithmetic subdivision in furtherance of computation of rigorous error bounds on integrated digital scene information for two dimensional display is provided. More particularly, a first aspect of the subject process includes pseudo-randomly subdividing an interval domain comprising a set of interval variables in furtherance of ascertaining a characteristic contribution of the interval variables of said set of interval variables to an image space comprising at least a sub-pixel area. A further aspect, either alone or in combination with the first aspect contemplates pseudo-randomly discarding a select partitioning of interval variables of a set of interval variables of a geometric function from a computed solution of an interval arithmetic branch-and-bound process.

Abstract: A method for binarizing a scanned document images containing gray or light colored text printed with halftone patterns. The document image is initially binarized and connected image components are extracted from the initial binary image as text characters. Each text character is classified as either a halftone text character or a non-halftone text character based on an analysis of its topology features. The topology features may be the Euler number of the text character; a text character with a Euler number below ?2 is classified as halftone text. The gray-scale document image is then divided into halftone text regions containing only halftone text characters and non-halftone text regions. Each region is binarized using its own pixel value statistics. This eliminates the influence of black text on the threshold values for binarizing halftone text. The binary maps of the regions are combined to generate the final binary map.

Abstract: Methods, systems, and media for image processing using hierarchical expansion are provided. More particularly, the hierarchical expansion can include a merge expansion and/or a refine expansion. In some embodiments, a method for image processing, comprising: receiving a plurality of images, wherein each of the plurality of images has one of a plurality of resolutions; for a first image from the plurality of images that has a first resolution, determining a first set of labels corresponding to each pixel of the first image; and for a second image from the plurality of images that has a second resolution, generating a second set of labels corresponding to each pixel of the second image based on the first set of labels.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving image data corresponding to an image, processing the image data to identify one or more features within the image, generating one or more keywords based on each of the one or more features, transmitting the one or more keywords to a computing device for displaying a list of the one or more keywords to a user, receiving text, the text comprising at least one keyword of the one or more keywords, that at least one keyword having been selected by the user from the list, and transmitting the image and the text for display, the text being associated with the image.

Abstract: Foreground objects of interest are distinguished from a background model by dividing a region of interest of a video data image into a grid array of individual cells that are each smaller than that a foreground object of interest. More particularly, image data of the foreground object of interest spans a contiguous plurality of the cells. Each of the cells are labeled as foreground if accumulated edge energy within the cell meets an edge energy threshold, if color intensities for different colors within each cell differ by a color intensity differential threshold, or as a function of combinations of said determinations in view of one or more combination rules.

Abstract: A method for rib suppression in a chest x-ray image detects and labels one or more ribs in a region of interest and detects rib edges of the one or more detected ribs. Cross rib profiles are generated along the detected ribs. The original x-ray image is conditioned according to at least one of the detected rib edge and cross rib profiles. The conditioned x-ray image can be stored, displayed, or transmitted.

Abstract: Methods, systems, and articles of manufacture for annotating of an image are disclosed. These include scoring the image using a plurality of trained classifiers, wherein each of the trained classifiers corresponds to at least one of a plurality of image groups clustered based upon image similarity, and wherein each image group is associated with a set of weighted labels; selecting one or more of the image groups based upon the scoring; aggregating one or more sets of weighted labels associated with the selected one or more image groups; and annotating the image using the aggregated one or more sets of weighted labels.

Abstract: In one embodiment, the invention provides a method, comprising detecting data fields on a scanned document image; generating a flexible document description based on the detected data fields, including creating a set of search elements for each data field, each search element having associated search criteria; and training or modifying the flexible document description using, for example, a search algorithm to detect the data fields on additional training images based on the set of search elements.

Abstract: An image recognition device that improves the accuracy of generic object recognition compared with conventional technologies by reducing the influence of the position, size, background clutter and the like of an object that is targeted to be recognized in the input image by the generic object recognition. The image recognition device performs a generic object recognition and includes: a segmenting unit configured to segment an input image into a plurality of regions in accordance with meanings extracted from content of the input image; a generating unit configured to compute feature data for each of the plurality of regions and generate feature data of the input image reflecting the computed feature data; and a checking unit configured to check whether or not a recognition-target object is present in the input image in accordance with the feature data of the input image.

Abstract: An image editing application (or a blur classification module thereof) may automatically estimate a coherent defocus blur map from a single input image. The application may represent the blur spectrum as a differentiable function of radius r, and the optimal radius may be estimated by optimizing the likelihood function through a gradient descent algorithm. The application may generate the spectrum function over r through polynomial-based fitting. After fitting, the application may generate look-up tables to store values for the spectrum and for its first and second order derivatives, respectively. The use of these tables in the likelihood optimization process may significantly reduce the computational costs of a given blur estimation exercise. The application may minimize an energy function that includes a data term, a smoothness term, and a smoothness parameter that is adaptive to local image content. The output blur map may be used for image object depth estimation.

Abstract: Approaches to segmentation or detection of objects and their boundaries in images (or other data sets) do not rely on machine learning approaches that aim to minimize pixel-level agreement between a computer and a human. Optimizing such pixel-level agreement does not, in general, provide the best possible result if boundary detection is a means to the ultimate goal of image segmentation, rather than an end in itself. In some examples, end-to-end learning of image segmentation specifically targets boundary errors with topological consequences, but otherwise does not require the computer to “slavishly” imitate human placement of boundaries. In some examples, this is accomplished by modifying a standard learning procedure such that human boundary tracings are allowed to change during learning, except at locations critical to preserving topology.

Abstract: An image processing device has an affinity calculating unit that handles each pixel in an image or each region including a plurality of pixels joined together, as a unit component, and determines a first affinity between each of the unit components and one of the unit components which is located in a periphery region of the image, a foreground region identifying unit that identifies, as a foreground region, a region made up of one or more of the unit components whose first affinities calculated by the affinity calculating unit are lower than a preset threshold, and a saliency measure output unit that determines a second affinity between each of the unit components in the image and the foreground region identified by the foreground region identifying unit, and outputs the second affinity as a saliency measure for each unit component.

Abstract: An image segmentation method includes generating a hierarchy of regions by unsupervised segmentation of an input image. Each region is described with a respective region feature vector representative of the region. Hierarchical structures are identified, each including a parent region and its respective child regions in the hierarchy. Each hierarchical structure is described with a respective hierarchical feature vector that is based on the region feature vectors of the respective parent and child regions. The hierarchical structures are classified according to a set of predefined classes with a hierarchical classifier component that is trained with hierarchical feature vectors of hierarchical structures of training images. The training images have semantic regions labeled according to the set of predefined classes. The input image is segmented into a plurality of semantic regions based on the classification of the hierarchical structures and optionally also on classification of the individual regions.

Abstract: A method for processing an electronic document is provided. The electronic document includes a plurality of text fields and a text label associated with each of the plurality of text fields. The method includes step of extracting the plurality of text fields from the electronic document. The method includes step of grouping the plurality of extracted text fields to generate a plurality of groups. The method includes step of labeling the plurality of groups based on a first pre-defined criteria to generate a plurality of labeled groups. The method includes step of distributing the plurality of labeled groups in a plurality of queues based on a second pre-defined criteria. The method includes step of transmitting the plurality of labeled groups from the plurality of queues to one or more crowdworkers based on a third pre-defined criteria.

Abstract: A system includes a content evaluation device is configured to receive reproduced media content and compare the reproduced media content to reference media content to determine a quality of the reproduced media content relative to the reference media content. The content evaluation device is configured to apply an entropy factor to the determined quality to model human perception of the reproduced media content. A method of determining the entropy factor includes converting the reference media content or the reproduced media content to a grayscale image, counting a number of unique luminance values in the grayscale image, determining the total number of possible luminance values, and defining the entropy factor to be the number of total pixels compared relative to the maximum number of pixels represented by any single luminance value multiplied by the number of possible luminance values.

Abstract: The invention relates to methods for determining a logical structure of a document. The system stores a collection of models, each of which describes one or more possible logical structures. At least one document hypothesis is generated for the whole document. For each document hypothesis, the system verifies the document hypothesis on each page, for example, by generating at least one block hypothesis for each block in the document based on the document hypothesis, selecting a best block hypothesis for each block, selecting the model that corresponds to a best document hypothesis the document hypothesis that has a best degree of correspondence with the selected best block hypotheses for the document, and forming a representation of the document based on the best document hypothesis described.

Abstract: A method and apparatus are provided for determining a descriptor for a region of interest in an image. The method includes defining a grid of points for the region of interest. A respective zone of influence is associated with each point of the grid of points. A representative value is determined for each point of the grid of points as a function of its respective zone of influence. The representative value obtained for each point of the grid of points is compared with at least one reference value. The result of the comparison serves to define a descriptor for the region of interest.

Abstract: Provided are an image processing apparatus, a region determining method and a computer-readable, non-transitory medium that can appropriately determine a cutting off region from a read image. The image processing apparatus includes an edge pixel extractor for extracting edge pixels from an input image, a region detector for detecting a subject region surrounded by connected edge pixels among the edge pixels, a straight line detector for detecting a plurality of straight lines within the subject region, a rectangle region detector for detecting a rectangle region formed of four straight lines where two straight lines each are substantially at right angles to each other among the plurality of straight lines, and a region determination module for determining the rectangle region as a cutting off region from the input image when the rectangle region and the subject region are substantially the same.

Abstract: A method embodiment herein begins by capturing a source image. The source image is segmented into first planes. The first planes can each comprise a mask plane and foreground plane combination. The binary images in the first planes are structurally analyzed to identify different regions of text, tables, handwriting, line art, equations, etc., using a document model that has information of size, shape, and spatial arrangement of possible regions. Then, the method extracts (crops out) these regions from the foreground plane to create second mask/foreground plane pairs. Thus, the method creates “second” planes from the first planes, so that a separate second plane is created for each of the regions. Next, tags are associated with each of the second planes (to create tagged mask/foreground plane pairs) and the second planes and associated tags are combined into a mixed raster content (MRC) document.

Abstract: An image processing apparatus sections an image to be processed into a plurality of blocks, rearranges the blocks into positions specified by an encryption key that uniquely specifies the positions of the blocks in the image, determines a computing method used to convert pixel values of pixels that form a minimum area included in each of the blocks after the blocks are rearranged based on the pixel values of predetermined pixels that do not belong to the minimum area, and converts the pixel values based on the computing method.

Abstract: Methods, systems, and media for image processing using hierarchical expansion are provided. More particularly, the hierarchical expansion can include a merge expansion and/or a refine expansion. In some embodiments, a method for image processing, comprising: receiving a plurality of images, wherein each of the plurality of images has one of a plurality of resolutions; for a first image from the plurality of images that has a first resolution, determining a first set of labels corresponding to each pixel of the first image; and for a second image from the plurality of images that has a second resolution, generating a second set of labels corresponding to each pixel of the second image based on the first set of labels.

Abstract: A device and method for dynamically adapting spatial resolution for imager Fourier transform spectrometers makes it possible to acquire data in interferogram mode and image mode on survey points for an observed scene, each survey point being associated a matrix of macro-pixels and defined by a plurality of zones. For each survey point, analysis of the content of each zone is carried out on the basis of data of the image mode. Classification into clear zone or non-clear zone is carried out as a function of proportion of cloud, and clear-pixel data are generated on the basis of the sum of the data of the macro-pixels of the clear zone class. Survey point data are generated on the basis of the sum of the data of all the macro-pixels of the matrix associated with the survey point. The survey point and clear pixel data streams are transmitted to the ground.

Abstract: A MMR system for publishing comprises a plurality of mobile devices, an MMR gateway, an MMR matching unit and an MMR publisher. The mobile devices send retrieval requests including image queries and other contextual information. The MMR gateway processes the retrieval request from the mobile devices and then generates an image query that is passed on to the MMR matching unit. The MMR matching unit receives an image query from the MMR gateway and sends it to one or more of the recognition units to identify a result including a document, the page and the location on the page. The MMR matching unit includes an image registration unit that receives new content from the MMR publisher and updates the index table of the MMR matching unit. A method for automatically registering images and other data with the MMR matching unit, a method for dynamic load balancing and a method for image-feature-based queue ordering are also included.

Abstract: An information processing device includes: a document receiving unit that receives a document containing at least one page, wherein positions of document components of a page of the at least one page are fixed within the page; a page dividing unit that divides the document received by the document receiving unit into at least one page; a page heading determining unit that determines a heading of a page of the at least one page divided by the page dividing unit based on components included in the page; and a processing unit that assigns the heading determined by the page heading determining unit to the page divided by the page dividing unit as first level outline information of the page.

Abstract: A method for detecting touch-point coordinates includes: scanning a plurality of signal points in sequence to generate a plurality of original data including a plurality of original touch point data; performing a grouping algorithm for the original touch point data to group the original touch point data into a plurality of group sets; and calculating a barycentric coordinate of each of the group sets and outputting the barycentric coordinate as a touch-point coordinate of each of the group sets.

Abstract: Systems and methods analyze the physical structure of text rows in a document image, including the positions of one or more alignments of one or more character blocks in one or more text rows of the document image. The systems and methods determine one or more groups of text rows that are placed into a class based on the structures of the text rows, such as the positions of the one or more alignments of the one or more character blocks in each text row.

Abstract: A controlling device may perform an image process on specific image data so as to generate processed image data, select a process mode from a plurality of process modes, including a first process mode and a second process mode, and perform the image process according to the selected process mode. The first process mode may be for performing the image process by performing, in order to compensate variability of discharging amounts of the liquid droplets discharged from the plurality of nozzles, a specific process on a target pixel within target image data using correction data for a target nozzle. The target nozzle may be to form a dot at a position on a print medium corresponding to the target pixel. The second process mode may be for performing the image process by performing the specific process on the target pixel within target image data without using the correction data for the target nozzle.

Abstract: Embodiments disclosed include methods and systems for assigning one or more labels to one or more segments of data received in an incoming segment to a line buffer for propagated component labeling, including preventing repeated labels in each line of the line buffer by assigning a different label for each of the one or more segments of data received in each line; labeling the incoming segment of the one or more segments of data by adopting a label of an overlapping segment on a prior received line when the overlapping segment does not overlap any other segment of data; labeling the incoming segment of the one or more segments of data by adopting a label of an overlapping segment on a prior received line when the overlapping segment overlaps more than one segment on the incoming segment when the segment is a first segment in the line buffer; and labeling the incoming segment of the one or more segments of data by adopting a label of a last overlapping segment when more than one segment overlaps the incoming s

Abstract: Site modeling using image data fusion. Geometric shapes are generated to represent portions of one or more structures based on digital height data and a two-dimensional segmentation of portions of the one or more structures is generated based on three-dimensional line segments and digital height data. A labeled segmentation of the one or more structures is generated based on the geometric shapes and the two-dimensional segmentation. A three-dimensional model of the one or more structures is generated based on the labeled segmentation.

Abstract: Disclosed are methods and systems of processing work flow associated with a print job including Specialty Imaging such as UV and/or IR encoding. According to one exemplary embodiment, a printing system controller accesses a spatially structured ink composed of a plurality of non-overlapping primitive spot colors to render Specialty Imaging effects along with other images and text associated with the print job.

Abstract: An image recognition device that improves the accuracy of generic object recognition compared with conventional technologies by reducing the influence of the position, size, background clutter and the like of an object that is targeted to be recognized in the input image by the generic object recognition. The image recognition device performs a generic object recognition and includes: a segmenting unit configured to segment an input image into a plurality of regions in accordance with meanings extracted from content of the input image; a generating unit configured to compute feature data for each of the plurality of regions and generate feature data of the input image reflecting the computed feature data; and a checking unit configured to check whether or not a recognition-target object is present in the input image in accordance with the feature data of the input image.

Abstract: A system and a method are provided for labeling images and for generating an annotation system. The labeling method includes providing a graphical structure, such as a tree structure, which graphically represents predictive correlations between labels in a set of labels. The predictive correlations can, for example, estimate the likelihood, in a training set, that knowing one label has a given value, another label will have a given value. An image to be labeled is received. Feature-based predictions for values of labels in the set of labels are computed for the image. A value for at least one label for the image from the set of labels is computed based on the feature-based label predictions and inference on the structured prediction model.

Abstract: An image processing apparatus includes a storage unit, a receiving unit, a search unit, a processing unit and an output unit. The storage unit stores information of drawn image elements. The receiving unit receives a transformation instruction to transform a part of the image elements specified by the information of the image elements. The search unit searches the storage unit for an image element that (i) has a relation, being based on a predetermined condition, with the image elements, which are a target of the transformation instruction, and (ii) is not the target of the transformation instruction. The processing unit performs a transformation process on (i) the image elements, which are the target of the received transformation instruction, and (ii) the image element, which is found as the search result, based on the received transformation instruction. The output unit outputs the result of the transformation process.

Abstract: A method for automatic convergence of stereoscopic images is provided that includes receiving a stereoscopic image, generating a disparity map comprising a plurality of blocks for the stereoscopic image, clustering the plurality of blocks into a plurality of clusters based on disparities of the blocks, selecting a cluster of the plurality of clusters with a smallest disparity as a foreground cluster, determining a first shift amount and a first shift direction and a second shift amount and a second shift direction based on the smallest disparity, and shifting a left image in the stereoscopic image in the first shift direction by the first shift amount and a right image in the stereoscopic image in the second shift direction by the second shift amount, wherein the smallest disparity is reduced.

Abstract: A method, system and computer program for segmenting an image are provided. The system may include an image acquisition system for acquiring a plurality of images; and a processor for clustering pixels from one of the images into one or more segments, each segment being defined in a state of either stable, mesostable or unstable, the processor further performing the clustering by determining residual pixels changing by more than a predetermined threshold, grouping the determined residual pixels to form segments selected from the group of unstable and mesostable segments, determining depth for all unstable and mesostable segments, transitioning unstable segments to corresponding mesostable segments if the unstable segment is determined to have a valid depth, transitioning mesostable segments to corresponding stable segments upon a determination that one or more predetermined stability criteria have been met, and merging one or more stable and mesostable segments.