Abstract: Various embodiments of the present invention relate to a method, system and computer program product for detecting and recognizing text in the images captured by cameras and scanners. First, a series of image-processing techniques is applied to detect text regions in the image. Subsequently, the detected text regions pass through different processing stages that reduce blurring and the negative effects of variable lighting. This results in the creation of multiple images that are versions of the same text region. Some of these multiple versions are sent to a character-recognition system. The resulting texts from each of the versions of the image sent to the character-recognition system are then combined to a single result, wherein the single result is detected text.

Abstract: Present invention relates to a method and system for automatic searching for information on a network in response to an image query sent by a user. The image query includes an image that is captured by using a mobile communications device with a camera. The image is processed to detect the text present in it. The detected text is then recognized using an OCR. Subsequently, the text is searched for matches in the corresponding domain database, selected from the various domain databases present in the network. Thereafter, selected matches and additional related information is sent to the user.

Abstract: The present invention relates to a method, system, and a computer-readable storage medium containing executable instructions for delivering content to a communication device, in response to an image sent by the communication device. The received image is matched with a plurality of images, and, when a match is found for the received image, content corresponding to the matching image is delivered to the communication device. The plurality of images is stored in an image database, and the corresponding content is stored in a content repository. The present invention enables a content provider to automatically update the image database and the content repository without any human intervention.

Abstract: Various embodiments of the present invention relate to a method, system and computer program product for detecting and recognizing text in the images captured by cameras and scanners. First, a series of image-processing techniques is applied to detect text regions in the image. Subsequently, the detected text regions pass through different processing stages that reduce blurring and the negative effects of variable lighting. This results in the creation of multiple images that are versions of the same text region. Some of these multiple versions are sent to a character-recognition system. The resulting texts from each of the versions of the image sent to the character-recognition system are then combined to a single result, wherein the single result is detected text.

Abstract: Various embodiments of the invention describe a method, system and computer-readable storage medium containing instructions for improving the recognition of text present in an image. The image is processed by applying different operators to the image to obtain multiple processed versions of the image. Thereafter, characters and location information of the characters from each of the multiple processed versions of the image are obtained. The location information includes the pixel coordinates of the characters in the text. The text present in the image is edited, based on the relative location of the characters, to improve the recognition of the text in the image.

Abstract: Image-based searching for information on a network is provided in response to an image query sent by a user. The image query includes an image captured using a mobile communications device with a camera. The image is processed to detect any text present in the image, and any detected text can be analyzed using a process such as optical character recognition (OCR). The analyzed text is used to search for matches in at least one corresponding domain database, selected from various domain databases present in the network. Thereafter, one or more selected matches and any additional related information can be sent to the user as one or more results for the submitted image query.

Abstract: A method, system and computer program product for matching images is provided. The images to be matched are represented by feature points and feature vectors and orientations associated with the feature points. First, putative correspondences are determined by using feature vectors. A subset of putative correspondences is selected and the topological equivalence of the subset is determined. The topologically equivalent subset of putative correspondences is used to establish a motion estimation model. An orientation consistency test is performed on the putative correspondences and the corresponding motion estimation transformation that is determined, to avoid an infeasible transformation. A coverage test is performed on the matches that satisfy orientation consistency test. The candidate matches that do not cover a significant portion of one of the images are rejected. The final match images are provided in the order of decreasing matching, in case of multiple images satisfying all the test requirements.

Abstract: A method, system and computer program product for representing an image is provided. The image that needs to be represented is represented in the form of a Gaussian pyramid which is a scale-space representation of the image and includes several pyramid images. The feature points in the pyramid images are identified and a specified number of feature points are selected. The orientations of the selected feature points are obtained by using a set of orientation calculating algorithms. A patch is extracted around the feature point in the pyramid images based on the orientations of the feature point and the sampling factor of the pyramid image. The boundary patches in lo the pyramid images are extracted by padding the pyramid images with extra pixels. The feature vectors of the extracted patches are defined. These feature vectors are normalized so that the components in the feature vectors are less than a threshold.

Abstract: Methods and systems, including computer program products, for determining a plurality of color clusters based on a plurality of pixels associated with a color image, the clusters being fewer than the pixels. A grayscale value for each one of a plurality of points in a color space is determined. Each grayscale value is based on a weighted average of target differences between each point and the clusters. Each of the pixels is associated with one or more of the points. A grayscale value for each pixel is identified based on the grayscale value of the associated one or more points.

Abstract: One embodiment of the present invention provides a system that efficiently performs a belief-propagation (BP) operation. During this process, for each node i in a BP graph, the system iteratively performs the following operations. First, the system receives incoming messages mji at node i for all adjacent nodes j. Next, the system calculates the full product Pi of all incoming messages mji. The system then produces an outgoing message mij from node i to node j by, computing a partial product Pij of all incoming messages to node i except for the message from node j by dividing the Pi by the incoming message from node j. The system then combines Pij with a data function for node i and a smoothness function between node i and node j to produce outgoing message mij. Finally the system communicates outgoing message mij to node j.

Abstract: One embodiment of the present invention provides a system that uses directional weighting functions while computing optical flow for an image through belief propagation. The system operates by computing local velocity estimates for points in the image. The system also computes directional weighting functions for points in the image, wherein the directional weighting functions facilitate propagating information in a manner which can vary with direction. The system subsequently uses these directional weighting functions during a belief propagation process, which propagates the local velocity estimates between points in the image, and which computes an optical flow field for points in the image.