Shoeprint wear area detection and stroking method

Abstract

The invention provides a shoeprint wear area detection and stroking method. The shoeprint wear area detection and stroking method comprises: preprocessing read-in image features to obtain an area of interest of a to-be-processed image; detecting a specific point set of the preprocessed image by using a multi-scale Gaussian difference operator; performing conditional screening on the specific pointset to obtain a candidate point set; preliminarily drawing a worn mask by adopting a bilateral region growing method based on gray scale and space distance; removing solid small patterns by adoptinga connected domain-based condition screening method; and performing wear degree grading according to the entropy of the preprocessed image area corresponding to each connected area, and performing labeling of different colors according to grading boundaries. According to the method, the worn part of the sole pattern can be effectively detected, the boundary can be accurately described, the methodhas good adaptability to different types of sole patterns, in the suspect footprint analysis and recognition process, workers are better assisted in shoeprint comparison and analysis more quickly, andthe effect more reliable than that of manual measurement is achieved.

Description

technical field [0001] The present invention relates to the technical field of shoe print recognition, in particular, to a method for detecting and tracing a worn area of ​​a shoe print. Background technique [0002] Existing shoe print comparative analysis systems generally extract wear characteristics indirectly, and rarely detect wear. The Chinese patent with the application number 201510472283.4 proposes that the two trace images to be identified are divided into different wear areas based on prior knowledge, and then the features of each partition area are extracted, and the respective values ​​of the two trace images to be identified are calculated. The normalized correlation coefficient of the part partition is used as the similarity of each part of the part, and the weighted sum of the similarity of each part is calculated as the feature similarity of the rough part of the part. When the similarity of coarse partition features is less than the threshold, it indicate...

AI Technical Summary

Problems solved by technology

[0003] First of all, the extracted features are general, and the extraction and detection of wear features are not targeted. In the comparison and analysis process, the abstracted numbers cannot correspond to the wear features in the physical real world, so the wear features cannot be analyzed specifically.

also can't get accurate results

Second, the specific boundaries of the wear area are not given

In addition, more complex operations such as the determination of the degree of wear cannot be realized

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