Abstract: A method and system for implementing character recognition is described herein. An input character is received. The input character is composed of one or more logical structures in a particular layout. The layout of the one or more logical structures is identified. One or more of a plurality of classifiers are selected based on the layout of the one or more logical structures in the input character. The entire character is input into the selected classifiers. The selected classifiers classify the logical structures. The outputs from the selected classifiers are then combined to form an output character vector.

Abstract: An optimization system comprises a reception component that receives a cascade of classifiers. The system further includes an optimization component communicatively coupled to the reception component, the optimization component receives input relating to one of speed and accuracy of the cascade of classifiers and optimizes the cascade of classifiers based at least in part upon the received input and confidence scores associated with each classifier within the cascade of classifiers. The optimization component can utilize at least one of a steepest descent algorithm, a dynamic programming algorithm, a simulated annealing algorithm, and a branch and bound variant of a depth first search algorithm in connection with optimizing the cascade of classifiers.

Abstract: What is disclosed is acquiring information regarding a web page, without having to commit to downloading that page. In one embodiment, after a current web page is downloaded from one source, and information regarding web pages linked to by links in the current web page are downloaded from a second source, when a user hovers a cursor over a link on a current web page, an informational region is displayed by the link that includes the information from the second source. The informational region may include, for example, a text box that apparently floats by the link. The information in the region can include, for example, keywords in the meta tags of the web page; paragraph headings of the web page; links on the web page to other pages; etc.

Abstract: Systems and methods are described that facilitate performing feature extraction across multiple received input features to reduce computational overhead associated with feature processing related to, for instance, optical character recognition. Input feature information can be unfolded and concatenated to generate an aggregated input matrix, which can be convolved with a kernel matrix to produce output feature information for multiple output features concurrently.

Abstract: Systems and methods for encoding and decoding document images are disclosed. Document images are segmented into multiple layers according to a mask. The multiple layers are non-binary. The respective layers can then be processed and compressed separately in order to achieve better compression of the document image overall. A mask is generated from a document image. The mask is generated so as to reduce an estimate of compression for the combined size of the mask and multiple layers of the document image. The mask is then employed to segment the document image into the multiple layers. The mask determines or allocates pixels of the document image into respective layers. The mask and the multiple layers are processed and encoded separately so as to improve compression of the document image overall and to improve the speed of so doing. The multiple layers are non-binary images and can, for example, comprise a foreground image and a background image.

Abstract: Systems and methods are disclosed that facilitate normalizing and beautifying digitally generated handwriting, such as can be generated on a tablet PC or via scanning a handwritten document. A classifier can identify extrema in the digital handwriting and label such extrema according to predefined categories (e.g., bottom, baseline, midline, top, other, . . . ). Multi-linear regression, polynomial regression, etc., can be performed to align labeled extrema to respective and corresponding desired points as indicated by the labels. Additionally, displacement techniques can be applied to the regressed handwriting to optimize legibility for reading by a human viewer and/or for character recognition by a handwriting recognition application. The displacement techniques can comprise a “rubber sheet” displacement algorithm in conjunction with a “rubber rod” displacement algorithm, which can collectively preserve spatial features of the handwriting during warping thereof.

Abstract: A system and method facilitating document image compression utilizing a mask separating a foreground of a document image from a background is provided. The invention includes a pixel energy analyzer adapted to partition regions into a foreground and background. The invention further provides for a merge region component adapted to attempt to merge regions if the merged region would not exceed a threshold energy. Merged regions are partitioned into a new foreground and new background. Thereafter, a mask storage component stores the partitioning information in a binary mask.

Abstract: A system and method for labeling radicals in East Asian characters is described. The identity of the radical and the location of the radical in a character may be stored for future reference.

Abstract: A computer-implemented word processing system comprises an interface component that receives a features vector associated with an electronic document. An analysis component communicatively coupled to the interface component analyzes the features vector and determines a viewing mode in which to display the electronic document. In accordance with one aspect of the subject invention, the viewing mode can be one of a conventional viewing mode and a viewing mode associated with enhanced readability.

Abstract: The subject invention relates to facilitating text detection. The invention employs a boosted classifier and a transductive classifier to provide accurate and efficient text detection systems and/or methods. The boosted classifier is trained through features generated from a set of training connected components and labels. The boosted classifier utilizes the features to classify the training connected components, wherein inferred labels are conveyed to a transductive classifier, which generates additional properties. The initial set of features and the properties are utilized to train the transductive classifier. Upon training, the system and/or methods can be utilized to detect text in data under text detection, wherein unlabeled data is received, and connected components are extracted therefrom and utilized to generate corresponding feature vectors, which are employed to classify the connected components using the initial boosted classifier.

Abstract: The subject invention leverages a scalable character glyph hash table to provide an efficient means to identify print characters where the character glyphs are identical over independent presentation. The hash table allows for quick determinations of glyph meta data as, for example, a pre-filter to traditional OCR techniques. The hash table can be trained for a particular environment, user, language, character set (e.g., alphabet), document type, and/or specific document and the like. This permits substantial flexibility and increases in speed in identifying unknown glyphs. The hash table itself can be composed of single or multiple tables that have a specific optimization purpose. In one instance of the subject invention, traditional OCR techniques can be utilized to update the hash tables as needed based on glyph frequency. This keeps the hash tables from growing by limiting updates that reduce its performance, while adding frequently determined glyphs to increase the pre-filter performance.

Abstract: A system and method facilitating image retouching is provided. The invention includes an image retoucher having a boundary detector and an image extender. The invention provides for the image retoucher to extend care pixels of at least one of a foreground and a background near a detected spurious boundary by altering the binary mask used for compression of the foreground and/or the background.

Abstract: A system and method facilitating pattern recognition is provided. The invention includes a pattern recognition system having a convolutional neural network employing feature extraction layer(s) and classifier layer(s). The feature extraction layer(s) comprises convolutional layers and the classifier layer(s) comprises fully connected layers. The pattern recognition system can be trained utilizing a calculated cross entropy error. The calculated cross entropy error is utilized to update trainable parameters of the pattern recognition system.

Abstract: A system and method to facilitate pattern recognition or matching between patterns are disclosed that is substantially invariant to small transformations. A substantially smooth deformation field is applied to a derivative of a first pattern and a resulting deformation component is added to the first pattern to derive a first deformed pattern. An indication of similarity between the first pattern and a second pattern may be determined by minimizing the distance between the first deformed pattern and the second pattern with respect to deformation coefficients associated with each deformed pattern. The foregoing minimization provides a system (e.g., linear) that may be solved with standard methods.

Abstract: A system and method facilitating image smoothing is provided. The invention includes an image processor having an image receptor and an image smoother. The invention provides for the image smoother to alter the value of a don't care pixel based, at least in part, upon a weighted average of care pixels.

Abstract: Electronic ink layout analysis systems and methods provide flexibility and efficiency in organizing, analyzing, and processing digital ink. These layout analysis systems and methods allow users substantial freedom in entering electronic ink into a pen-based computer system. Using these systems and methods, a user's input digital ink is not constrained by requirements that a user write in a specific screen orientation, that a user write in one specific orientation on all portions of a page, or that a user write using a specific minimum or maximum sized stroke. Rather, the systems and methods freely allow the user to write anywhere on a given page, in any orientation or size, while still enabling effective and efficient handwriting recognition and other processing of the input digital ink.

Abstract: Systems and methods for performing adaptive filtering are disclosed. The present invention generates probabilities that can be used in an encoder, such as an arithmetic encoder and generates those probabilities in a computationally efficient manner. Probabilities of previously encoded coefficients are employed, effectively, in generating probabilities of the coefficients without regard to directional information. Thus, a large amount of information is adaptively and efficiently used in generating the probabilities. For the coefficients, the probability is computed based at least partly on at least one probability of a previously computed probability of a neighboring coefficient. Then, the coefficients are encoded using those computed probabilities.

Abstract: A system and method to facilitate pattern recognition or matching between patterns are disclosed that is substantially invariant to small transformations. A substantially smooth deformation field is applied to a derivative of a first pattern and a resulting deformation component is added to the first pattern to derive a first deformed pattern. An indication of similarity between the first pattern and a second pattern may be determined by minimizing the distance between the first deformed pattern and the second pattern with respect to deformation coefficients associated with each deformed pattern. The foregoing minimization provides a system (e.g., linear) that may be solved with standard methods.

Abstract: Systems and methods for performing clustering of a document image are disclosed. A property of an extracted mark from a document is compared to the properties of the existing clusters. If the property of the mark fails to match any of the properties of the existing clusters, the mark is added as a new cluster to the existing cluster. One property that can be utilized is x size and y size, which is the width and height, of the existing clusters. Another property that can be employed is ink size, which refers to the ratio of black pixels to total pixels in a cluster. Yet another property that can be utilized is a reduced mark or image, which is a pixel size reduced version the bitmap of the mark and/or cluster. The above properties can be employed to identify mismatches and reduce the number of bit by bit comparisons performed.

Abstract: A global optimization framework for optical character recognition (OCR) of low-resolution photographed documents that combines a binarization-type process, segmentation, and recognition into a single process. The framework includes a machine learning approach trained on a large amount of data. A convolutional neural network can be employed to compute a classification function at multiple positions and take grey-level input which eliminates binarization. The framework utilizes preprocessing, layout analysis, character recognition, and word recognition to output high recognition rates. The framework also employs dynamic programming and language models to arrive at the desired output.