Grg Banking Equipment Co., Ltd.

Weifeng Wang

Tiancai Liang

Kun Wang

Yuanchao Yu

Rongqiu Wang

Dingxi Chen

Siwei Liu

Panfeng Luo

Mengtao Liu

Xiaoliang Wang

Xinhua Qiu

A method and a device for adaptively recognizing a value document are provided. The method includes: acquiring a collection parameter, and collecting a photoelectric signal of the value document; acquiring a photoelectric signal correction amount, and performing digital compensation on the photoelectric signal; performing feature extraction on the photoelectric signal subjected to the digital compensation to obtain a feature vector; inputting the feature vector to a preset classifier for recognition, to obtain a recognition result of the value document; acquiring a specific region on the value document; acquiring feature information of the photoelectric signal of the value document; calculating an accumulation component and a differential error of the value document; calculating a total correction amount of the photoelectric signal; updating the photoelectric signal correction amount and the collection parameter; and outputting the recognition result.

Self-adaptive identification method of identifying negotiable instrument and device

Provided is a character segmentation and recognition method. The method includes: collecting image data to obtain a to-be-recognized image; positioning a character line candidate region on the to-be-recognized image; obtaining pre-set character line prior information, where the character line prior information includes the number of characters, character spacing and a character size; obtaining a corresponding segmentation point template based on the character line prior information; obtaining credible degrees of different positions on the character line candidate region traversed by the segmentation point template; determining a position with the highest credible degree as an optimal segmentation position; segmenting the character line candidate region based on the segmentation point template and the optimal segmentation position to obtain multiple single character regions; and performing character recognition on each of the single character regions to obtain a corresponding recognition result.

Character segmentation and recognition method

A banknote recognition and classification method and system are provided. In the method and system, a large number of reliable samples which are easy to acquire currently are used to establish a sample signal degradation model which meets application requirements by means of a statistical method, sample information is input into the banknote sample signal degeneration model to acquire various banknote sample information corresponding to the brand new banknotes to be learned; the various banknote sample information is input to perform classifier learning, and a banknote classification model is output; then a classifier learns to perform classification and recognition on a sample to be recognized.

Banknote recognition and classification method and system

The present invention relates to a character recognition method. Same comprises: step 1: reading in a character image; step 2: image preprocessing; step 3: character splitting; step 4: edge extraction; utilizing an edge detection operator to detect edge points of characters; step 5: feature extraction, where the features of each edge point of each character are all expressed with distances running from other edge points of the character to the edge point and are represented by eigenvectors (P, P, . . . P); step 6: feature processing, mapping the eigenvectors (P, P, . . . P) into a matrix, T, thus allowing all characters to be identical in eigenvector dimension; and, step 7: template matching recognition. Because the features of each edge point of the characters are all expressed with the distances running from the other edge points to the edge point, the entirety of the features are ensured for the characters, and the difference in features are expanded for different characters, thus increasing character recognition accuracy.

Character recognition method

An anti-counterfeiting feature generation method for a valuable document and an authentication method and device therefor. The anti-counterfeiting feature generation method for a valuable document uses the anti-counterfeiting feature information redundancy to hide accurate information about an anti-counterfeiting feature. In the generation method, the anti-counterfeiting feature of a valuable document has little change on the human perception, but a valuable document authentication device in a financial self-service equipment can effectively extract the hidden accurate information about an anti-counterfeiting feature from signals obtained by a sensor and conduct quantitative detection and authentication, thereby effectively authenticating whether the valuable document is counterfeit or not. A new anti-counterfeiting feature which facilitates machine recognition is loaded to the valuable document, and a corresponding valuable document authentication device is configured to a financial self-service equipment, so that the financial self-service equipment can read the anti-counterfeiting feature of the valuable document by facilitating machine recognition, thereby improving the authentication accuracy of the financial self-service equipment to the valuable document.

Anti-counterfeiting feature generation method for valuable document and authentication method and device therefor

A valuable document authentication method and device. Whether a valuable document, an image sensor or a first sensor has shifted or not, the effect of authenticating the valuable document will not be affected, because a reference unit is needed to determine the location relationship between the image sensor and the first sensor before the valuable document is authenticated, thereby preventing an error occurring with the authenticated valuable document due to the fact that each sensor has shifted; moreover, when the valuable document is authenticated, even if the valuable document has shifted, the correctness of the valuable document authenticated can also be guaranteed by the conversion of the location relationship between a detection object and the sensor. Therefore, the solution provided in the present invention improves the identification accuracy and working efficiency of the authentication device, thereby providing convenience for users.

Valuable document authentication method and device

The present invention relates to a recognition method and a recognition device for a sheet-type medium. The method comprises: step, collecting image information; step, splitting from the image information collected image information of an object-to-be-recognized; step, reconstructing image data of a feature area, extracting a feature on the reconstructed image data, and forming an eigenvector; and, step, sending the eigenvector into a standard data-trained classifier, and acquiring a recognition result. The method has an image reconstructed on the basis of feature area prior information, improves image quality, facilitates increased recognition accuracy, and, because only the image area that requires feature extraction is reconstructed, reduces storage space consumption. This not only saves large amounts of storage space and time and increases resource utilization rate, but also increases recognition accuracy and achieves an improved balance between resource and efficiency.

Recognition method and recognition device for sheet-type medium

A paper identifying method and a related device, used for accurately identifying soilage conditions of paper according to the recency degree of the paper. The method in an embodiment of the present invention comprises: obtaining a pixel gray value group of an image of input paper, the pixel gray value group being a combination of gray values of sampled pixels of a specified region of the input paper; obtaining an average value of gray values of all pixels in the pixel gray value group, and using same as a first average gray value; comparing the first average gray value with a recency threshold to determine the recency level of the input paper; obtaining the soilage depth of each of N regions of the input paper, the N being an integer greater than or equal to 1; and determining the soilage level of the input paper according to the soilage depth of the N regions, the region area and a soilage threshold, the soilage threshold corresponding to the recency level.

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Guangzhou, China

Weifeng Wang