Abstract: A method and associated device wherein an inverse histogram based pixel mapping step is combined with an edge enhancement step such as unsharp masking. In such an arrangement the inverse histogram based pixel mapping step improves the performance of the unsharp masking step, serving to minimize the enhancement of noise components while desired signal components are sharpened.

Abstract: A brightness control apparatus comprising a probability density function (PDF) calculator to calculate a PDF based on pixel values of respective pixels of an input image signal, a first setter to set an upper limit value and a lower limit value with respect to the pixel values that are equal to or smaller than a predetermined level in the PDF, and a brightness value controller to calculate a cumulative distribution function for the PDF controlled by the upper and lower limit values set by the first setter, and calculating brightness levels corresponding to the input image signal based on the calculated cumulative distribution function. The brightness control apparatus controls the brightness of an image signal so as to prevent it from becoming unnecessarily bright or dark when compensating the brightness of an image signal, while also preventing degradation of contrast.

Abstract: Image data provided from a scanner is simultaneously supplied to page memory and a reference value calculating section. The reference value calculating section creates a density histogram of the document image on the basis of image data corresponding to a predetermined number of image lines and calculates a set of correction reference values for pixel density correction using the density histogram. A range correcting section corrects pixel density indicated by the image data on all the image data read out from the page memory by using the set of correction reference values. The predetermined number of image lines is a fraction of all the image lines of the document image read by the scanner.

Abstract: The present invention provides to image processing methods that include a method of selecting an optimal threshold value (to) for an image comprising the steps of: obtaining an image; selecting a test segment of the said image; determining the mean feature size (S) of features appearing in the test segment at each of a plurality of threshold values (t), so as to produce mean feature size data (S(t)); selecting a relevant subset of the mean feature size data (S(t)); and determining an optimal threshold value (to) as a function of said subset of the mean feature size data. The present invention additionally provides methods of thresholding an image to produce a binary image by application of the optimal threshold value (to) determined according to the methods of the present invention.

Abstract: A halftone gradation processing method reduces or eliminates the discontinuous gradation reproduction in comparison with conventional error diffusion. A halftone gradation processing method includes obtaining a position and a pixel value of a target pixel in an input image, correcting the pixel value, selecting the closest threshold to the corrected pixel value from among usable thresholds assignable to the pixel value, calculating an error between the corrected pixel value and the selected threshold, and diffusing the error around the target pixel, the pixel value correcting being corrected by the diffused error, and the selected threshold being output to an output device which may handle the assigned thresholds.

Abstract: The present invention provides to image processing methods that include a method of selecting an optimal threshold value (tO) for an image comprising the steps of: obtaining an image; selecting a test segment of the said image; determining the mean feature size (S) of features appearing in the test segment at each of a plurality of threshold values (t), so as to produce mean feature size data (S(t)); selecting a relevant subset of the mean feature size data (S(t)); and determining an optimal threshold value (tO) as a function of said subset of the mean feature size data. The present invention additionally provides methods of thresholding an image to produce a binary image by application of the optimal threshold value (tO) determined according to the methods of the present invention.

Abstract: A color image processing apparatus for digitally reading a color document and effecting digital printing comprises a character region extracting device for extracting a character region of the color document; a black portion extracting device for extracting a black portion of the color document; and a single black color processing device for processing a single black color only with respect to a region which falls within the character region and the black portion in the color document, so as to allow character portions to be distinguished favorably.

Abstract: A technique is disclosed for identifying potentially defective circuitry associated with discrete pixel regions in an imaging system detector. Signals representative of the pixels in an image matrix are generated. The signals are analyzed to identify mean and standard deviation values from a histogram of the pixel population. Pixels lying outside of a desired range, such as a distribution envelope determined from the histogram, are compared to the mean value plus or minus a multiple of the standard deviation. Pixels lying outside of the desired range are labeled or masked as potentially defective.

Abstract: In an image processing technique for binarizing an image scanned by a shuttle type scanner in a multifunctional machine using a small amount of memory, after scanning pixels of one slice from a document, each pixel of the scanned slice are binarized using a mask. The processing results of the error values generated during binarizing of final pixels of a plurality of slices of the band are stored in a first memory, and the processing results of error values generated during binarizing of each of the pixels of the scanned slice are stored in a second memory. When each of the first pixels of a plurality of slices in the next band are binarized, the processing results of the error values of the final pixels of a plurality of slices in the previous band, stored in the first memory, are scanned and then binarized. By using minimum band memories, the cost of the multifunctional machine can be reduced.

Abstract: The read out image data is stored in the mask memory in a predetermined mask unit, and binarized into binary value with a predetermined threshold in the binarizing circuit. The binarized image data is output to the main scanning direction-black pixel counting circuit and the sub scanning direction-black pixel counting circuit, respectively, to count black pixels in the main scanning direction and in the sub scanning direction, respectively. The largest value is determined by the comparator, and designated as the linkage degree. With the judging circuit, the area judgement of the character area, the photograph area and the dot area is performed based on the linkage degree.

Abstract: A system and method for processing image data from a document and for producing a compressed binarized version of the image data for transmission to or use by subsequent users. Processing of the image data is done in parallel after the scanning of the document is started but before the entire document is scanned. A splitter is used to divide a scan line of image data produced by an imager at the scan line into a plurality of channels, with each channel having at least one overlap area of pixels and with the overlap areas of pixels being used to avoid errors between channels. Thresholding and compression are performed by each one of the channels in parallel. The compression is performed in a direction which is perpendicular to the direction of scanning and conforms to a standard compression algorithm like CCITT Group 4.

Abstract: Image data for continuous three pixels delayed by one pixel from each other is input in row and column directions from an image input portion into a scanning window. A predetermined image pattern is stored in a count value comparison table for detecting a target pixel on an image contour, and a determining portion performs determination relating to the predetermined image pattern and the input image data. Based on the result of determination by the determining portion, an intensity converter portion performs conversion of intensity data such that the target pixel becomes black when the target pixel is present on the image contour, and that the target pixel becomes white in other cases. As a result, an image processing apparatus can output a smooth contour image without jaggies regardless of an input image intensity.

Abstract: An image processing method and device computes the image quality as an evaluation value, determine the image quality based on this evaluation value, and employ a restoration process in accordance with image quality when this image quality is poor.

Abstract: A bi-level image is pre-processed by dividing the image into rectangular blocks, and rearranging the dots in each rectangular block into a pattern determined by the density of black dots in the block. The resulting rearranged image is suitable for further processing such as resolution conversion or compressive encoding.

Abstract: What is disclosed is a mapping circuit configured to map a range of captured intensity values to a companded intensity level based upon the density of captured intensity values present in the captured image. Also provided is a companding circuit coupled to the mapping circuit, the companding circuit configured to replace each pixel of the captured image with a corresponding mapped intensity value pixel. The companding circuit and mapping circuit are configured to preserve image characteristics.

Abstract: Embodiments of the invention include a method and apparatus for determining values for data reproduced or retrieved from data storage media such as in holographic memory systems. The method includes initially approximating the value of data members retrieved initially from the data storage medium of interest (e.g., by their intensity levels based on an absolute scale), using those approximations collectively to establish one or more threshold levels for defining ranges for the data values to be determined, and determining values for the retrieved data members by comparing the initial data value approximations of the retrieved data members to the established threshold levels. Alternatively, the threshold level(s) are set initially and adjusted iteratively based on the initial approximations of the individual data members until a final established threshold level is established.

Abstract: The image correlation method and apparatus correlates or matches a test image with a template. The image correlation apparatus includes an image processor for partitioning the template into a number of labels, for determining the total number of pixels N.sub.T which form the template and for determining the number of pixels N.sub.i which form each of the labels i. The image correlation apparatus also includes comparison means for comparing the test image to the template. The comparison means determines, for each predetermined gray level j, the number of pixels of the test image N.sub.j,i representative of a predetermined gray level j which correspond to a predetermined label i of the template. The comparison means also determines, for each predetermined gray level j, the number of pixels of the test image N.sub.j representative of a predetermined gray level j which correspond to the template.

Abstract: Image analysis methods and systems are used for identifying objects in a background by defining a data space, such as a histogram or a color space. The data space comprises a plurality of sub-spaces, which could be selected based, for example, on a histogram, or on the way pixel values or color parameters cluster in their respective spaces. The threshold values in the data space are selected, a list of all ordered pairs of thresholds is generated to define multiple data sub-spaces, and the image is multiply searched, once in each sub-space for at least one representation of a candidate object, where the candidate object has at least one predetermined attribute value. Valid objects are identified by comparing the candidate object attribute values to a defined set of valid object attribute values contained in a driver.

Abstract: A novel analogue to digital (A/D) converter semiconductor integrated circuit intended for digitizing signals generated by a physical stimulus sensing electronic apparatus, and more particularly, for digitizing signals generated by an array of photo-integrator circuits of an active pixel sensor (APS) imaging device. The A/D converter is a modified single slope integration type, wherein the reference ramp signal exhibits predetermined nonlinearity and offset. The nonlinearity and offset of the reference ramp signal track the nonlinearity and offset components in the signal being digitized, the latter being nonlinearity and offset components contributed by sources appearing in advance of the A/D conversion point in the signal acquisition and processing path of a digital camera system.

Abstract: An image enhancing method using a mean-separate histogram equalization method is disclosed. An input image signal is divided into two sub-images in a picture unit according to a mean level of the input image signal. Then, cumulative density functions for each of the sub-images are calculated. Afterwards, the input sample is mapped into two gray levels, each of which belongs to a first range and a second range, by using first and second transform functions defined by use of the cumulative density functions, respectively. Finally, one of two mapped levels is selected depending on the magnitude of the input sample. As a result, the brightness of the given image can be preserved while the contrast is enhanced.

Abstract: A machine vision method is provided for segmenting an image based on an adaptive thresholding approach that exploits prior knowledge of the characteristics, such as area, of the object to be segmented. Adaptation to varying gray-values of the candidate object/background from scene-to-scene is obtained by using a sampling window which provides gray-value statistics of the candidate object to be segmented. Next, using these statistics, a characteristic of the image of the object to be segmented, such as its area or its gray-value standard deviation, and the histogram of the image, the segmentation is performed. The invention is especially useful for detecting the presence/absence of adhesive on printed circuit boards, where both the appearance of the printed circuit board and the solder paste commonly found thereon make segmentation difficult. In case of presence/absence determination, an additional step of shape matching is employed.

Abstract: An image processing method and device computes the image quality as an evaluation value, determine the image quality based on this evaluation value, and employ a restoration process in accordance with image quality when this image quality is poor.

Abstract: A multi-stage, preprocessing technique increases the quality of a monochrome or colored mixed-mode document printed on a binary-type printer. The document is preferably apportioned into a plurality of small tiles, each of which provides information to the inventive technique for eventually defining the modes as either text or images. The multi-stage technique comprises a first stage for normalizing a non-ideal histogram of the mixed-mode document to a histogram having an ideal distribution of selected pixel values. A second stage classifies each tile as either text, image or background, while a third stage collates groups of tiles in both vertical and horizontal directions to remove variances in the document. Those portions of the document classified as images are then halftone processed, while the text areas are threshold processed to thereby significantly improve the reproduction quality of the printed document.

Abstract: An object of the present invention is to provide an image processing apparatus that reads density unevenness contained in the image, based on the base density of the image data and performs density data correction.

Abstract: A binarization circuit compares the density value of the target pixel with the density value of surrounding pixels in the vicinity. A judging unit judges whether or not the target pixel is isolated from the surrounding pixels. A detection unit detects the density values of the target pixels which make the target pixels isolated by a binarization process. A calculation unit calculates the accumulated isolated pixel frequencies of each density value detected by the detecting function when the judging unit and the detecting unit have finished processing all of the original image. A determination unit determines a threshold value on the basis of the accumulated isolated pixels frequencies.

Abstract: A method of multithresholding a document image considers both local and global information in determining the number of thresholded levels contained in a gray-scale image. A gray-scale image is comprised of a plurality of pixels. Each pixel has an intensity value. Local regions of pixels having similar intensity values are identified and compiled into a global representation of the image. Intensity ranges are identified in the global representation in which the number of regions of pixels are approximately constant. An intensity value is identified within each range which represents the most constant point within the representation range. The number of threshold levels is set equal to the number of ranges in the representation.

Abstract: A method and apparatus for cropping an image in digital form. The image to be cropped is represented as a first digital array which is operated on by an edge enhancement transformation to generate a second, binary digital array wherein edges of the image are emphasized. The second digital array is then partitioned into predetermined segments which are typically rows and columns of the array and the pixel values of each row and column are summed to generate brightness sums. The second digital array is then partitioned into a first, brighter, central group of rows and a second, less bright group consisting of upper and lower borders of rows; and a third, brighter, central group of column and left and right borders of columns in accordance with predetermined criteria relating to the brightness sums.

Abstract: An image processing method and device computes the image quality as an evaluation value, determine the image quality based on this evaluation value, and employ a restoration process in accordance with image quality when this image quality is poor.

Abstract: A method and apparatus for the analysis and correction of the image gradation of an image original to be reproduced by evaluating image values acquired by point-by-point and line-by-line, optoelectronic scanning with an input device in apparatus and systems for image processing. The image original is geometrically subdivided into a plurality of sub-images. The frequency distribution of the image values or, respectively, of the luminance components of the color values in a corresponding sub-image is separately identified as a sub-image histogram. The sub-image histograms of the individual sub-images are evaluated and the sub-images relevant for the image gradation are identified by means of the evaluation. An aggregate histogram that corresponds to the frequency distribution of the image values or, respectively, of the luminance component of the color values in the relevant sub-images is calculated from the sub-image histograms of the relevant sub-images.

Abstract: An apparatus comprising a scanner, a histogram preparation circuit, a circuit for analyzing a histogram to calculate a background density of a document and a character density, a circuit for correcting an input pixel density based on the background density and character, and a printer for forming an image based on a corrected pixel density. The histogram preparation circuit prepares a density histogram of each scanning line based on the pixel density input from the scanner, and accumulates a frequency (number of pixels) corresponding to each density. However, the frequency of the histogram, which is prepared up to the previous scanning line, is multiplied by a weighting factor in accordance with the number of scanning lines, and the frequency of the histogram of the present scanning line, is also multiplied by a weighting factor in accordance with the number of scanning lines. Thereafter, the results of the multiplication are added, and the density histogram is prepared.

Abstract: A white-level correction circuit for an analog-to-digital converter which converts an analog image signal of a pixel, which is input from an external source, to digital image data based on white-level reference voltage and black-level reference voltage inputs. The white-level correction circuit stores white-level reference data for the pixel in a memory and reads the data from the memory in synchronization with the input of the analog image signal. A digital-to-analog converter converts the read white-level reference data to an analog signal comprising the white-level reference voltage. The digital image data is decoded and white-level reference voltage correction data is generated by correcting the read white-level reference data, based on the decoded digital image data, and the white-level correction data is stored in the memory.

Abstract: The present invention relates to an image analysis method and system for identifying objects in a background by generating a description, which in this case is a co-occurrence matrix, of the gray level space of the image by using an entropic kernel to recursively analyze the gray level space for candidate objects and validating the presence of valid objects by comparing the candidate object attribute values to a defined set of valid object attribute values contained in a driver. The present invention includes recursive, iterative and parallel processing methods. The methods may be used in a wide variety of industrial inspection techniques, including colony counting and the identification of discrete features in carpets and of pigment elements embedded in a polymer.

Abstract: In a method of measuring noise in image signals, a number of noise estimates (SAD) is calculated (1). Subsequently, it is determined (3-9) which noise estimation interval [A, B] out of a plurality of predetermined noise estimation intervals [A, B] contains at least a predetermined number of noise estimates (SAD) and has at the same time the lowest upper interval boundary. The output noise measurement value depends on the determined noise estimation interval.

Abstract: A computer-based system and method automatically determines a threshold level for each cell of a digital document having one or more cells. Each cell of the document has a plurality of pixels and each pixel has associated therewith a plurality of bits to represent a graylevel for that pixel. A co-occurrence matrix indicating a quantity of each pixel graylevel pair in the cell is constructed. From this matrix, a first histogram is constructed and used to determine a background and a foreground peak for the cell and the features for these peaks. The center of mass for the cell is determined based on these features and is used to determine the threshold level for the cell.

Abstract: A method for the automated detection of gross abnormalities and asymmetries in chest images, including generating image data from radiographic images of the thorax. The image data are then analyzed in order to produce the boundaries of the aerated lung regions in the thorax. This analysis comprises location of the mediastinum and lung apices, iterative global thresholding with centroid testing of contours, local thresholding on regions along initial contours of the aerated lung, correction for regions near the costo- and cardiophrenic angles in the chest, analysis of the areas and density distribution within the aerated lung regions in the chest and determination of the likelihood of the presence of a gross abnormality or asymmetry. Final output could be the computer determined contours of the lungs or the likelihood for abnormality.

Abstract: The problem of thresholding is considered from a clustering point of view and a novel weight-based clustering method (WCThresh) is implemented in a neural network image processor 50. The neural network image processor 50 uses weights 51-53, representing clusters of gray scale pixels of an image of document 43, to provide a threshold for the image of document 43. The processor 50 modifies weights 51-53 with the input pixels and comparator 60 using a nearest value criterion to provide the threshold.

Abstract: An image reading apparatus includes an image sensing unit for photoelectrically reading an original image, and outputting an image signal, a converter unit for converting the image signal from the image sensing unit into density data representing density levels of a plurality of steps, a detection unit for detecting frequencies of appearance in units of density levels of the density data from the converter unit, and a correction unit for correcting the density levels expressed by the density data from the converter unit on the basis of the frequencies of appearance detected by the detection unit.

Abstract: This specification discloses a process and system for processing a digitally stored image on a digital computer. The system scans and digitizes an image, separate text from non-text components, enhances and deskews the image, compresses the resulting image file, and stores the enhanced, deskewed, and compressed file for later transmission, optical character recognition, or high quality printing or viewing of the image.

Abstract: A method for the adaptive quantization of the range of input values on the basis of the histogram method for estimating density. Input values are read-in and assigned to a quantization of the range of input values. From the distribution of the input values, a density-estimate function is determined which is transformed into a monotonically rising mapping function. The range of values of the mapping function is divided into equally sized sub-ranges which are translated into corresponding partitions in the range of input values. A new quantization of the range of input values is achieved which distributes the limited number of partitions so that a large number of small partitions are assigned to ranges of large fluctuations in the input-value distribution, and a small number of large partitions are assigned to ranges of small fluctuations in the input-value distribution.

Abstract: In a thresholding method for segmenting gray scale image which is less dependent on the concentration distribution of the input image, the threshold in determined as a zero-cross point of a histogram difference between the concentration histograms for the gray scale image within the window at a window position at which the window contains more high concentration region and at a window position at which the window contains more low concentration region. Also, in a method of determining a background concentration distribution from an image having an arbitrarily distributed pattern, the background concentration level is determined as a peak concentration or a mean value concentration of a low concentration section of the histogram difference of the concentration histograms for two associated windows. Also.

Abstract: To reliably discriminate the characters only from the headlines having any background textures, the present invention analyzes the projection profile of a grey image in a headline area in order to automatically set a learning area A in the area of background texture only of the periphery in the headline area, and set a learning area B in the area that includes background texture of a central portion and characters; determines a discriminant function having, as variables, characteristics that use a plurality of pixel densities in the vicinity of a pixel which is processed so that output values of the discriminant function at each of the positions in the learning area A forms a profile with an average Va, that the output values at each of the positions in the learning area B forms a profile with an average Vb, and that the sum of dispersion values of the two profiles becomes smaller than a predetermined value, in order to discriminate in which area is included the pixel which is processed in the headline area;

Abstract: A method of picture image processing, and system for carrying out same, involves generation of a composite mapping function, for transforming gray scale values to different values in order to enhance contrast. A reduced range histogram is generated, involving removing a percentage of the total histogram counts from bottom and top sub-ranges and also removing spikes. The reduced histogram is then density averaged in order to obtain a first map function. A second map function is generated for interfacing with the characteristics of the printer to be used, and a composite mapping transform is generated by combining the two generated functions. After the composite mapping function is generated, each gray value of the image data set is transformed in accordance with the composite function, for use in printing, thereby providing an enhanced contrast image.