Konica Minolta Laboratory U.s.a., Inc.

Konica Minolta Systems Laboratory, Inc.

Other

Yibin Tian

Wei Ming

Thang Duong

Xiaonong Zhan

A method, a computer program product, and a system for analyzing exam-taking behavior and improving exam-taking skills are disclosed, the method includes obtaining a student answering sequence and timing to an examination having a series of questions; comparing the student answering sequence and timing with results from a statistic analysis of the examination obtained from a plurality of students; and identifying an abnormality in the student answering sequence and timing according to the comparison.

Method and system for analyzing exam-taking behavior and improving exam-taking skills

A method, computer program product, and a system for enhancing an interaction between a teacher and a student are disclosed, the method includes receiving video images of a region of interest from a plurality of multi-functional devices; comparing the video images of the region of interest received from the plurality of multi-functional devices; detecting differences in the region of interest of at least one multi-functional device in comparison to the region of interest of the plurality of multi-functional devices; and providing a signal to the at least one multi-functional device based on the detected difference in the region of interest.

Method and system for enhancing interactions between teachers and students

A method for compressing a bi-level document image containing text is disclosed. The document image is segmented into symbol images each representing a letter, numeral, etc. in the document. The symbol images are classified into a plurality of classes, each class being associated with a template image and a class index. Classification is done by comparing each symbol to be classified with template of existing classes, using a number of image features including zoning profiles, side profiles, topology statistics, and low-order image moments. These image features are compared using a tolerance based method to determine whether the symbol matches the template. After classification, certain classes that have few symbols classified into them may be merged with other classes. In addition, the template images of the classes are down-sampled, where the final sizes of the template images are dependent on the likelihood of confusion of the template with other templates.

Document image compression method and its application in document authentication

A method for authenticating a printed document which carries barcode that encode authentication data, including word bounding boxes for each word in the original document image and data for reconstructing the original image. The printed document is scanned to generate a target document image, which is then segmented into text words. The word bounding boxes of the original and target document images are used to align the target document image. Then, each word in the original document image is compared to corresponding words in the target document image using word difference map and Hausdorff distance between them. Symbols of the original document image are further compared to corresponding symbols in the target document image using feature comparison, symbol difference map and Hausdorff distance comparison, and point matching. These various comparison results can identify alterations in the target document with respect to the original document, which can be visualized.

Method of authenticating a printed document

A simple, fast, and effective method is provided for background removal for document images with dark text over relatively uniform or slow-varying non-white background. Candidate regions for background removal are first identified by binarizing the input gray-scale image using a global threshold very close to white. Large contours in the binarized image are identified as candidate regions. A histogram analysis is applied to preliminarily identify regions containing graphics, which are excluded from further processing. The remaining candidate regions are individually binarized. The binarized regions are analyzed to determine whether they contain graphics or text/table, by examining their geometric characteristics and statistics of connected components within them. For candidate regions determined to contain text or tables, background pixels in the input image are set to white using a mask which is the inverse of the individually binarized images of the regions. Regions that contain graphics are left unchanged.

Background removal for document images

In a document image enhancement method, text character strokes are enhanced in a way such that areas closer to the center (skeleton) of each stroke are enhanced (e.g. made darker) by greater amounts than areas farther away from the center. Each text or line region of the input image is first binarized to generate a binary image containing connected components corresponding to character strokes and lines. Multiple levels of pseudo-skeletons are computed for each connected component, for example by using successive thinning. Multiple pseudo-skeleton difference areas, i.e. differences between successive levels of pseudo-skeletons, are generated. Pixels located in different pseudo-skeleton difference areas are enhanced by different amounts, by applying different inverse-degradation functions. Graphical regions of the input image may be treated with edge enhancement.

Pseudo-skeleton based image enhancement for document image reproduction

A method for encoding and decoding color barcodes to increase their data capacity. The encoding steps include determining a shape, a foreground color and a background color for each data cell, wherein a combination of the shape, foreground and background colors for the data cell is chosen from a plurality of such combinations in accordance with a value of the digital data to be encoded; and coloring some pixels in the data cell with a foreground color and other pixels with a background color, in accordance with the shape, foreground and background colors for the data cell determined above. The decoding steps include segmenting the data cells, recognizing a shape, a foreground color of the shape and a background color of the data cell, and obtaining digital data from a combination of the shape and foreground and background colors in each data cell.

Four dimensional (4D) color barcode for high capacity data encoding and decoding

A document authentication method employs Krawtchouk decomposition to analyze and compare document images. When printing an original document, the original document image is segmented into image patches, which preferably correspond to individual symbols of the document. Krawtchouk decomposition is applied to each image patch. The image patches are classified into image patch classes using their Krawtchouk coefficients. The locations of all image patches belonging to each class are obtained and stored along with the Krawtchouk coefficients for each class. When authenticating a target document, the same segmentation, Krawtchouk decomposition and classification steps are applied to the target document image, and the locations of all image patches belonging to each class are obtained. The image patch classes and the locations of image patches belonging to each class for the original and target document image are compared to detect alterations present in the target document.

Method and system for document authentication using Krawtchouk decomposition of image patches for image comparison

A method for separating foreground and background contents in a document image is provided. The method first computes a pixel-wise map of maximal local features (e.g., local variance, local contrast, etc.), which is binarized to generate a mask for potential foreground. In order to utilize color information effectively, the local feature map is computed using all color channels of the image. Then the background image is obtained by inpainting the mask regions from the non-mask regions of the original document image. Adaptive thresholding is applied to the difference between the original document image and the background image to obtain the binary foreground image. Post-processing of the binary foreground image can further remove undesirable elements. Finally, a more accurate background image can be obtained by inpainting the original document image using the binary foreground image as a mask.

Color document image segmentation and binarization using automatic inpainting

A binary image downsampling method, including the steps of generating a gray-scale image from a binary image having a background and one or more foreground portions, locating skeleton pixels in the one or more foreground portions, manipulating values of certain foreground pixels in the gray-scale image such that the differences between the values of the skeleton pixels and the background pixels become more significant, downsampling the gray-scale image with the manipulated values of the certain foreground pixels, and generating a downsampled binary image from the downsampled gray-scale image.

Topology-preserving downsampling of binary images

A method and program for encoding and decoding color barcodes to increase their data capacity. The encoding steps include determining a shape and a color for each data cell to encode digital data, wherein a combination of the shape and the color for the data cell is chosen from a plurality of combinations of shapes and colors in accordance with a value of the digital data to be encoded, and coloring a subset of the plurality of pixels in each data cell in accordance with the shape and the color for the data cell determined above. The decoding steps include segmenting the data cells in a color barcode, recognizing a shape formed by a subset of pixels in each data cell and the color of the shape, and obtaining digital data from a combination of the recognized shape and color in each data cell.

A method for decoding digital data in a color barcode having a plurality of data cells, including the steps of: scanning the color barcode of the hardcopy document, separating color image of the color barcode into print primary color planes, computing peaks of each print primary color plane, projecting, for at least one of the print primary color planes, the data cells along a horizontal direction and a vertical direction at the peaks of the at least one of the primary color planes in each direction which represent data cell center locations respectively, and creating a grid where each of its intersection is a respective data cell center location, assigning a color to each grid intersection which corresponds to a respective data cell by examining values of the print primary color planes at such location, and decoding digital data from the data cells based on the respective color assigned to each data cell.

Robust decoding of color barcode printed with extremely small data cells

A method is described for binarizing a gray scale document image, in particular, a document image containing both text and non-text contents. Phase congruency maps are calculated from the gray scale image, and used to segment the text and non-text areas of the gray scale image. The phase congruency maps are also used to extract long lines such as table lines, which can be optionally removed from the image. The text and non-text areas of the gray scale image are divided into image patches; for the text areas, connected components obtained from the phase congruency map are used to generate image patches, so that each image patch contains a text character. The image patches are binarized individually using individual threshold values, and then combined to generate a binary image of the gray scale image. The method can also be used for purposes of OCR or document authentication.

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Menlo Park, CA, United States of America

Yibin Tian