Abstract: A new method for accurately identifying key information in financial bill images under the interference of stains is proposed to solve the problem of recognition failure caused by local information loss or misjudgment during the recognition of financial bill information containing stains. By integrating the gray scale and denoising of the image, dividing the bill area according to the threshold size, binary processing is achieved. Using the ROI (Region of Interest) principle, rough screening of information range is performed in the binary processed image to calculate the maximum coverage contour and key information adhesion area. Further segmentation and edge calibration are performed, and key information areas are located based on the ROI ratio. The features of key information areas is extracted, classification labels in an end-to-end manner are established by combining the features, and the recognition target is searched according to the label gradient in the coverage recognition area. The experimental results show that the retrieval rate obtained by the proposed method is between 80%-100%, and the efficiency is greatly improved with superior and reliable performance. 

Key words: financial receipts, image stains, key information, accurate identification, identification method, defect localization