The invention relates to a hierarchical scanning, automatic identification and
processing method based on
traffic violation snapshot pictures, and belongs to the field of
image processing and
traffic management. The technical method aims at improving the scanning efficiency, accurately recognizing
traffic violation information and achieving
automatic processing and uploading so as to improve the
processing efficiency and accuracy of
traffic violation snapshot data. Comprising the steps of hierarchical scanning, automatic identification,
data verification and uploading, and
exception handling and feedback. According to the method, the stored snapshot pictures are quickly positioned and extracted by presetting the folder hierarchy depth and being compatible with various folder hierarchy structures, and each picture is marked, so that repeated scanning and missing detection are avoided, and the scanning efficiency is remarkably improved. The OCR technology is combined with the
deep learning algorithm, so that the recognition accuracy is remarkably improved, and particularly, error recognition can be effectively reduced in a complex environment. After identification is completed, the
system verifies the accuracy of an identification result through an automatic
verification mechanism, seamless connection and
processing of data are completed, manual intervention is reduced, and law
enforcement efficiency is improved.