CAJ | 학술논문

局部二值模式(LBP)在人脸识别领域取得了显著成效,但由于没有考虑像素之间的对比度,导致部分重要纹理特征被丢弃.采用粗粒度分区算法求取各人脸分块对比度值域区间的动态阈值点,并借鉴LMCP算法思想利用上述阈值点分别对各人脸分块编码,得到结合光照变化信息的局部非线性多层对比度特征LNMCP作为人脸特征.实验结果表明,该方法识别率高,特别是在户外人脸库上提高了2.91%,方法在不可控光照变化环境下具有极强的自适应性.
국부이치모식(LBP)재인검식별영역취득료현저성효,단유우몰유고필상소지간적대비도,도치부분중요문리특정피주기.채용조립도분구산법구취각인검분괴대비도치역구간적동태역치점,병차감LMCP산법사상이용상술역치점분별대각인검분괴편마,득도결합광조변화신식적국부비선성다층대비도특정LNMCP작위인검특정.실험결과표명,해방법식별솔고,특별시재호외인검고상제고료2.91%,방법재불가공광조변화배경하구유겁강적자괄응성.
Local Binary Pattern(LBP)has been used with considerable success in face recognition field, while it hasn’t considered the contrast between pixels so that some important texture features have been abandoned. This paper proposes to calculate dynamic thresholds of the contrast range by coarse grain algorithm, and extracts the face feature with the thresholds, meanwhile the code method is similar to Local Multi-layer Contrast Pattern(LMCP). Moreover, Local Nonlinear Multi-layer Contrast Pattern(LNMCP) can get the face features, which contained the information of illumination various. The experiments show that the proposed method has a high recognition rate, the results on outdoor database can be enhanced by 2.91%especially. It proves that the method will be adaptive under uncontrollable varying illumination.