Research on the measurement method of barefoot footprint similarity

Huaice Liu; Ning Ding; Shancheng Lin; Hongyu Lv; Xinyan Liu

doi:10.1117/12.2656775

13 January 2023 Research on the measurement method of barefoot footprint similarity

Huaice Liu, Ning Ding, Shancheng Lin, Hongyu Lv, Xinyan Liu

Proceedings Volume 12510, International Conference on Statistics, Data Science, and Computational Intelligence (CSDSCI 2022); 125100I (2023) https://doi.org/10.1117/12.2656775
Event: International Conference on Statistics, Data Science, and Computational Intelligence (CSDSCI 2022), 2022, Qingdao, China

Abstract

The barefoot footprint is a common trace material evidence in the crime scene, and it is an important basis for investigating and solving the case. However, the identification of barefoot footprint is mostly realized by manual operation, which is easily affected by subjective factors. It is difficult to compare and identify a large number of barefoot footprint samples. This paper puts forward a variety of barefoot similarity measurement methods, and uses MATLAB software to realize the automatic segmentation, extraction and comparison of the physical and morphological features of barefoot footprints. After image binarization, open operation and closed operation by corrosion and expansion processing, convex hull operation, edge detection and so on, by using many kinds of similarity measurement methods, the features of the footprint can be extracted completely and calculated accurately. According to the measurement principle of different "distance" in computer vision image processing and machine learning, an algorithm is designed to measure the similarity of 120 barefoot footprint samples imprinted by the same person and different people. The accuracy of the algorithm is tested by comparing the calculation results, so that the algorithm can be applied in practice.

Citation Download Citation

Huaice Liu, Ning Ding, Shancheng Lin, Hongyu Lv, and Xinyan Liu "Research on the measurement method of barefoot footprint similarity", Proc. SPIE 12510, International Conference on Statistics, Data Science, and Computational Intelligence (CSDSCI 2022), 125100I (13 January 2023); https://doi.org/10.1117/12.2656775

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