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引用次数: 6
摘要
最近的趋势和统计数据表明,哈希概念已经变得越来越重要,因为它的应用是在认证、检索和识别领域。提出的认证哈希方法CCQ-CSLBP (Compressed CSLBP with Correlation Coefficient)利用相关系数作为CSLBP中的权重因子。CSLBP是一种纹理算子,在旋转不变性、微分幂和直方图bin数量较少等方面都优于LBP。在CSLBP中,每个子块的直方图用16个bin表示。通过翻转差分概念实现了直方图bin数量的减少。该方法在直方图构建过程中利用相关系数作为增强因子,提高压缩CSLBP的识别能力。随着相关系数的使用,CSLBP在TPR和FPR方面的结果有所改善。CCQ-CSLBP基于归一化汉明距离和ROC特征进行评估。
Recent trends and also statistics show that the hashing concept has been gaining importance because its application lies in the area of authentication, retrieval and recognition. The proposed hashing method CCQ-CSLBP (Compressed CSLBP with Correlation Coefficient) for authentication utilized correlation coefficient as a weight factor in CSLBP. CSLBP is a texture operator, whose performance is better than LBP, in terms of rotation invariance, differentiation power and less number of histogram bin. In CSLBP, histogram of each sub block is represented by 16 bin. Reduction in number of histogram bin is achieved by the flipped difference concept. Proposed method takes the advantage of correlation coefficient as a boosting factor during histogram construction, to increase the discrimination power of compressed CSLBP. With the use of correlation coefficient, results of CSLBP improved, in terms TPR and FPR. CCQ-CSLBP is evaluated, based on normalized hamming distance and ROC characteristics.