Multi-order texture features for palmprint recognition

Multi-order texture features for palmprint recognition
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用于掌纹识别的多阶纹理特征

DOI:
10.1007/s10462-022-10194-5
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发表时间:
2022-05
影响因子:
12
通讯作者:
Jun Chu
Jun Chu
中科院分区:
计算机科学2区
文献类型:
--
作者:
Ziyuan Yang;Lu Leng;Tengfei Wu;Ming Li;Jun Chu

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Palmprint attracts increasing attention thanks to its several advantages. 1st-order textures have been widely used for palmprint recognition; unfortunately, high-order textures, although they are also discriminative, were ignored in the existing works. 2nd-order textures are first employed for palmprint recognition in this paper. 1st-order textures are convolved with the filters to extract 2nd-order textures that can refine the texture information and improve the contrast of the feature map. Then 2nd-order textures are used to generate 2nd-order Texture Co-occurrence Code (2TCC). The sufficient experiments demonstrate that 2TCC yields satisfactory accuracy performance on four public databases, including contact, contactless and multi-spectral acquisition types. Moreover, in order to further improve the discrimination and robustness of 2TCC, we propose Multiple-order Texture Co-occurrence Code (MTCC), in which 1st-order Texture Co-occurrence Code (1TCC) and 2TCC are fused at score level. 1TCC is good at describing minor wrinkles; while 2TCC does well in describing principal textures. Thus the combination of both can describe the palmprint features more comprehensively. MTCC achieves remarkable accuracy performance when compared with the state-of-the-art methods on all public databases.
DOI: 10.1109/access.2021.3112513
发表时间: 2021
期刊: IEEE Access
影响因子: 3.9
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