The increasing use of invoicing has created an unnecessary burden on labor and material resources in the financial sector. This paper proposes a method to intelligently identify invoice information based on template matching, which retrieves the required information by image preprocessing, template matching, an optical character recognizing, and information exporting. The origin invoice image is preprocessed first to remove the useless background information by secondary rotation and edge cutting. Then, the region of the required information in the obtained regular image is extracted by template matching, which is the core of the intelligent invoice information identification. The optical character recognizing is utilized to convert the image information into text so that the extracted information can be directly used. The text information is exported for backup and subsequent use in the last step. The experimental results indicate that the method using normalized correlation coefficient matching is the best choice, demonstrating a high accuracy of 95%, and the average running time of 14 milliseconds. INDEX TERMS Invoice information identification, template matching, contour extraction, image processing, convolutional neural network.
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