A method and a system for fingerprinting signatures and enhanced signature capturing for charge card transactions on mobile communication devices identify and transform a signature into a normalized representation such as a bytestream including coordinate data and combine the normalized representation with some transaction information into combined data. The combined data is further transformed into fixed length data stored for further analyses or uses. Upon the receipt of a dispute, the stored representation(s) of the signature and some of the stored transaction information of the transaction in dispute may be transformed into a first fixed length data. The first fixed length data may be further compared with the stored fixed length data obtained at the time of the transaction to resolve the dispute. The representations of signatures of multiple transactions may be used to determine whether these multiple transactions belong to the same category or to different categories.

There are provided a comparison device and a comparison method including determining whether or not a comparison target person is a subject of a registered face image by comparing an imaged face image to the registered face image, of determining whether or not a blocking object is provided in the imaged face image, of determining whether or not removing the blocking object is required, by calculating a partial similarity score between the imaged face image and the registered face image in a partial area corresponding to the blocking object, and of urging the blocking object to be detached based on the partial similarity score.

Embodiments of a method and system described herein enable capture of video data streams from multiple, different video data source devices and the processing of the video data streams. The video data streams are merged such that various data protocols can all be processed with the same worker processors on different types of operating systems, which are typically distributed. In an embodiment the multiple video data sources comprises at least one mobile device executing a video sensing application that produces a video data stream for processing by video analysis worker processes. The processes include estimating a queue wait time.

A camera apparatus is provided for detecting a stream of objects moving relative to the camera apparatus having a plurality of individual cameras that each have an image sensor for recording frames, wherein the frames overlap one another in part, having an evaluation unit for compiling frames, and having a geometry detection sensor for detecting geometrical data of the objects. The evaluation unit is here configured to generate an object image assembled from frames of an individual object of the stream of objects, with the selection of the participating frames and/or the assembly taking place on the basis of the geometrical data.

A centrifugal protective hair blower, comprising a plastic shell for wrapping powered devices of the blower, wherein the plastic shell is made of polycarbonate casting; an electric heating device which is arranged in the plastic shell of the hair blower, composed of a two to three sections electric heating wire, and is used to control the blowing temperature of the hair blower; a hemispherical picture-shooting mechanism, which includes a trailing measurement device, an image interception device, a data analysis device, a DC drive motor, an optical filter, optical lens and an image sensing device; an electric heating device, which is connected with a vector analysis device, and is used to reduce the blowing temperature of the hair blower when the target type is a cat, a dog or a rabbit. Through the present invention, it is capable of preventing the hair blower from causing unwarranted injury to surrounding pets.

The disclosure provides a bill identification method, device, electronic device and a computer-readable storage medium. The method includes: obtaining an image of a bill to be identified; using a pre-trained area identification model to identify a final payment area of the bill in the image; using a pre-trained character identification model to identify the final payment amount in the final payment area. By applying the solution provided by the present disclosure, it is possible to realize automatic identification of the payment amount on the bill, and the efficiency of bill processing is improved.

An image processing device includes an image processing unit that performs image processing on an observed image in which a cell is imaged and an image processing method selector that is configured to determine an observed image processing method for analyzing the imaged cell on the basis of information of a processed image obtained through image processing of the image processing unit.

A method of image-to-document conversion based on optical character recognition (OCR) includes obtaining an image to be converted into a target document, and performing layout segmentation on the image according to image content of the image, to obtain n image layouts, each of the n image layouts corresponding to a content type, and n being a positive integer. The method also includes, for each of the n image layouts, processing image content in the respective image layout according to the content type corresponding to the respective image layout, to obtain converted content corresponding to the respective image layout. The method further includes adding the converted content corresponding to the n image layouts to an electronic document, to obtain the target document.

A computer-implemented method for identifying features of interest in a data image. The method includes identifying data variations in a data image or set of data images, each data image comprising rendered data, identifying one or more features of interest in the data image or set of data images based on the identified data variations, identifying a feature of interest genus corresponding to each identified feature of interest, reclassifying the rendered data based on each of the identified features of interest genuses so as to eliminate background data in the rendered data thereby producing an eliminated background dataset, and generating a feature of interest map for each identified feature of interest genus. A machine learning method, including a training phase, for automatically identifying features of interest in a data image is further provided.

A computer-implemented method for assessing if characters in a sample image are formed from a predefined font. The method comprises forming a first embedded space representation for the predefined font, extracting sample characters from the sample image, forming a second embedded space presentation of the sample characters, and comparing the first and second embedded space representation to assess if the sample characters are of the predefined font.