A multi-feature fusion approach to nasal pattern recognition

Fuding Chu; Ling Li

doi:10.1117/12.2683555

26 June 2023 A multi-feature fusion approach to nasal pattern recognition

Fuding Chu, Ling Li

Proceedings Volume 12721, Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023); 1272110 (2023) https://doi.org/10.1117/12.2683555
Event: 2023 2nd International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2023, Chengdu, China

Abstract

A nasal pattern recognition method based on multi-feature fusion is proposed to address the problems of imperfect feature information extraction, low recognition accuracy and interference of redundant information in nasal pattern images by a single method. An improved two-channel attention mechanism (I_CBAM) is introduced in the residual network to reduce the interference of redundant information; the output feature information of Layer2, Layer3 and Layer4 in the fusion depth residual network structure is used to enrich the extracted global features of the image by using the complementarity between feature maps of different scales; meanwhile, extract the underlying local features with better matching in the nasal pattern image using the improved SURF algorithm, and fuse the extracted global features with the local features; the training of the model is supervised using the improved fusion loss function. The experimental results on the nasal pattern dataset show that the recognition accuracy is improved compared with other mainstream recognition methods.

Citation Download Citation

Fuding Chu and Ling Li "A multi-feature fusion approach to nasal pattern recognition", Proc. SPIE 12721, Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 1272110 (26 June 2023); https://doi.org/10.1117/12.2683555

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