计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2015年
17期
177-181
,共5页
人脸识别%梯度%尺度块局部二值模式(LBP)%特征提取%直方图%降维
人臉識彆%梯度%呎度塊跼部二值模式(LBP)%特徵提取%直方圖%降維
인검식별%제도%척도괴국부이치모식(LBP)%특정제취%직방도%강유
face recognition%gradient%scaled-block Local Binary Pattern(LBP)%feature extraction%histogram%dimen-sionality reduction
针对方向边缘幅值模式（POEM）忽略了块与块之间的像素问题，提出一种基于方向边缘幅值的尺度块LBP人脸识别方法。该方法首先用梯度算子提取出人脸的方向图和幅值图，将具有相同量化方向上的幅值累加，然后利用尺度块LBP算子提取每幅累加幅值图的分块直方图特征，并将所有直方图特征串联起来作为最终的识别特征，最后采用WPCA降维方法提高算法的有效性。实验结果表明，该算法的鲁棒性高于其他对比算法，运用降维处理后能以较低的特征维数达到良好的识别性能。
針對方嚮邊緣幅值模式（POEM）忽略瞭塊與塊之間的像素問題，提齣一種基于方嚮邊緣幅值的呎度塊LBP人臉識彆方法。該方法首先用梯度算子提取齣人臉的方嚮圖和幅值圖，將具有相同量化方嚮上的幅值纍加，然後利用呎度塊LBP算子提取每幅纍加幅值圖的分塊直方圖特徵，併將所有直方圖特徵串聯起來作為最終的識彆特徵，最後採用WPCA降維方法提高算法的有效性。實驗結果錶明，該算法的魯棒性高于其他對比算法，運用降維處理後能以較低的特徵維數達到良好的識彆性能。
침대방향변연폭치모식（POEM）홀략료괴여괴지간적상소문제，제출일충기우방향변연폭치적척도괴LBP인검식별방법。해방법수선용제도산자제취출인검적방향도화폭치도，장구유상동양화방향상적폭치루가，연후이용척도괴LBP산자제취매폭루가폭치도적분괴직방도특정，병장소유직방도특정천련기래작위최종적식별특정，최후채용WPCA강유방법제고산법적유효성。실험결과표명，해산법적로봉성고우기타대비산법，운용강유처리후능이교저적특정유수체도량호적식별성능。
In order to solve the problem that POEM(Pattern of Oriented Edge Magnitudes)ignores the pixel among blocks, a new face recognition method based on scaled-block LBP of oriented edge magnitude is proposed. Firstly, the ori-entation and magnitude of a face are extracted by gradient operator. The magnitude is accumulated on the basis of orientation with the same quantitative value. Secondly, divided histograms are extracted from each accumulated magnitude encoded by the scaled-block LBP operator. All the histograms are cascaded as the final recognition feature. Finally, the dimension-ality reduction method of WPCA is used to improve the effectiveness of the proposed algorithm. Experimental result shows that the proposed algorithm is more robust than other comparing algorithms and can achieve good recognition per-formance with short dimension after feature dimensionality reduction method used.
