计算机应用与软件
計算機應用與軟件
계산궤응용여연건
COMPUTER APPLICATIONS AND SOFTWARE
2015年
4期
141-144
,共4页
人脸识别%韦伯局部描述符%支持向量机%直方图
人臉識彆%韋伯跼部描述符%支持嚮量機%直方圖
인검식별%위백국부묘술부%지지향량궤%직방도
Face recognition%Weber local descriptor%Support vector machine%Histogram
对WLD特征进行改进。改进的特征提取方法为:首先将原始人脸图像划分为若干个子块,然后提取每块图像的WLD直方图统计特征,其中的梯度方向是用Prewitt算子计算的,最后将所有分块的WLD直方图序列连接起来构成特征向量。为了验证改进特征的性能,用支持向量机进行人脸识别,人脸图像取自ORL和YALE人脸数据库。实验结果表明,采用改进后的特征可以显著提高人脸识别率。
對WLD特徵進行改進。改進的特徵提取方法為:首先將原始人臉圖像劃分為若榦箇子塊,然後提取每塊圖像的WLD直方圖統計特徵,其中的梯度方嚮是用Prewitt算子計算的,最後將所有分塊的WLD直方圖序列連接起來構成特徵嚮量。為瞭驗證改進特徵的性能,用支持嚮量機進行人臉識彆,人臉圖像取自ORL和YALE人臉數據庫。實驗結果錶明,採用改進後的特徵可以顯著提高人臉識彆率。
대WLD특정진행개진。개진적특정제취방법위:수선장원시인검도상화분위약간개자괴,연후제취매괴도상적WLD직방도통계특정,기중적제도방향시용Prewitt산자계산적,최후장소유분괴적WLD직방도서렬련접기래구성특정향량。위료험증개진특정적성능,용지지향량궤진행인검식별,인검도상취자ORL화YALE인검수거고。실험결과표명,채용개진후적특정가이현저제고인검식별솔。
We improve the Weber local descriptor (WLD)feature.The improved feature extraction method is that to divide the original face image into a number of blocks first,then to extract the histogram statistical characteristics of WLD in each block,in which the gradient orientation is computed by Prewitt descriptor,and finally to concatenate the WLD histograms series of all blocks to form eigenvector.In order to verify the performance of the improved WLD feature,we use support vector machine (SVM)for face recognition,the face images come from ORL and YALE face databases.Experimental results show that to use the improved WLD feature can significantly enhance the face recognition accuracy.