Methods and systems are described for automatically identifying and presenting to a user products or services related to an electronic image identified by the user. The products or services may further be related to a user selection of an object within the image. The image may be obtained from a web site accessed by the user, or the image may be captured by the user via a camera of a mobile device. The image or mobile device may be associated with a geographic location, which may be used to further improve product or service search accuracy. Labels associated with aspects of the image may be generated and used to further identify keywords for searching products or services. Genres may be determined from the keywords to identify vendors or order options to search. The search results may be presented to the user as options related to relevant products or services.

Methods and systems are described for automatically identifying and presenting to a user products or services related to an electronic image identified by the user. The products or services may further be related to a user selection of an object within the image. The image may be obtained from a web site accessed by the user, or the image may be captured by the user via a camera of a mobile device. The image or mobile device may be associated with a geographic location, which may be used to further improve product or service search accuracy. Labels associated with aspects of the image may be generated and used to further identify keywords for searching products or services. Genres may be determined from the keywords to identify vendors or order options to search. The search results may be presented to the user as options related to relevant products or services.

Methods and systems are described for automatically identifying and presenting to a user products or services related to an electronic image identified by the user. The products or services may further be related to a user selection of an object within the image. The image may be obtained from a web site accessed by the user, or the image may be captured by the user via a camera of a mobile device. The image or mobile device may be associated with a geographic location, which may be used to further improve product or service search accuracy. Labels associated with aspects of the image may be generated and used to further identify keywords for searching products or services. Genres may be determined from the keywords to identify vendors or order options to search. The search results may be presented to the user as options related to relevant products or services.

A method and a system of capturing an image of a card having a magnetic stripe is provided. The method includes obtaining a first image by an imaging device of the card, obtaining a plurality of images of the card via color delta analysis, and obtaining a third image of the card by comparing the first and the plurality of images.

A search area is set on a recognition target image, cutout areas are set at a plurality of positions in the search area, images corresponding to the plurality of set cutout areas are extracted, similarities of candidate characters obtained by comparison between the extracted images and dictionary data is weighted in accordance with the positions of the cutout areas. In such a manner, evaluation values of the candidate characters are obtained, and a candidate character with the highest evaluation value among the obtained candidate characters is output as a recognition result. Further, a search area relating to a next character is set based on position information about the cutout area corresponding to the recognition result.

An image processing apparatus determines whether each of pixels in a scanned image is a color pixel or a monochrome pixel, determines whether each of blocks including the multiple pixels in the scanned image is a color block or a monochrome block, based on determination results of the respective pixels, and determines that the scanned image is a color image in a case where an arrangement pattern of blocks determined to be color blocks matches a predetermined pattern.

According to one embodiment, a reading system includes a processing device. The processing device includes an extractor, a line thinner, a setter, and an identifier. The extractor extracts a partial image from an input image. A character of a segment display is imaged in the partial image. The segment display includes a plurality of segments. The line thinner thins a cluster of pixels representing a character in the partial image. The setter sets, in the partial image, a plurality of determination regions corresponding respectively to the plurality of segments. The identifier detects a number of pixels included in the thinned cluster for each of the plurality of determination regions, and identifies the character based on a detection result.

The present disclosure involves systems, software, and computer implemented methods for transaction auditing. One example method includes determining valid pixel-based pattern(s) that are included in valid reference images. Fraudulent pixel-based pattern(s) that are included in fraudulent reference images are determined. A request to classify an image is received. A determination is made as to whether pixel values in the image match a valid pixel-based pattern or a fraudulent pixel-based pattern. In response to determining that the pixel values match a valid pixel-based pattern, a likelihood of classifying the first image as a valid image is increased. In response to determining that the pixel values match a fraudulent pixel-based pattern, a likelihood that the image as a fraudulent image is increased. The image is classified in response to the request as either a valid image or a fraudulent image based on the likelihoods.

The present disclosure involves systems, software, and computer implemented methods for transaction auditing. One example method includes determining valid pixel-based pattern(s) that are included in valid reference images. Fraudulent pixel-based pattern(s) that are included in fraudulent reference images are determined. A request to classify an image is received. A determination is made as to whether pixel values in the image match a valid pixel-based pattern or a fraudulent pixel-based pattern. In response to determining that the pixel values match a valid pixel-based pattern, a likelihood of classifying the first image as a valid image is increased. In response to determining that the pixel values match a fraudulent pixel-based pattern, a likelihood that the image as a fraudulent image is increased. The image is classified in response to the request as either a valid image or a fraudulent image based on the likelihoods.

A text image processing method and a text image processing apparatus are provided. In some embodiments, a text image processing method includes: preprocessing a text image to obtain a binary image, where the binary image includes multiple connected regions; acquiring a convex hull corresponding to each of the connected regions with a convex hull algorithm; acquiring a character region circumscribing the convex hull; performing character segmentation on the acquired character region to obtain multiple character blocks; and merging the character blocks based on heights of the character blocks to obtain word blocks of the text image.