CAJ | 학술논문

为了增强掌纹图像信息的分析和提取能力，提出了一种基于轮廓与边缘纹理特征融合的掌纹识别算法。该算法分别将灰度直方图和差分盒子维算法作用于掌纹图像的低频和高频成分，提取图像的轮廓和边缘纹理特征，然后并联融合二者特征向量进行匹配。通过香港理工大学PolyU掌纹图像数据库的验证，算法识别精度为99.56%，特征提取和匹配时间为56 ms，满足识别精度和实时性要求，且算法复杂度和造价低，具有较高的工程应用价值。
위료증강장문도상신식적분석화제취능력，제출료일충기우륜곽여변연문리특정융합적장문식별산법。해산법분별장회도직방도화차분합자유산법작용우장문도상적저빈화고빈성분，제취도상적륜곽화변연문리특정，연후병련융합이자특정향량진행필배。통과향항리공대학PolyU장문도상수거고적험증，산법식별정도위99.56%，특정제취화필배시간위56 ms，만족식별정도화실시성요구，차산법복잡도화조개저，구유교고적공정응용개치。
In order to enhance the ability of analysis and extraction of palm print image information, this paper proposes a novel palm print recognition method based on contour feature and edge texture feature fusion. We choose grey histogram and differential box counting to work on low-frequency features and high-frequency, and extract its contour feature and edge texture features. Then, making two features fusion in parallel. Experimental results on PolyU palm print experiment and compares with the traditional palm print recognition algorithm, the proposed method can obtain 99.56% recognition accuracy and the time of feature extraction and matching is only 56 ms, meeting the real-time requirements. At the same time, with low algorithm complexity and low cost in the actual demand, and has high value of engineering application.