计算机应用与软件
計算機應用與軟件
계산궤응용여연건
COMPUTER APPLICATIONS AND SOFTWARE
2014年
10期
172-175
,共4页
Log-Gabor滤波器%人耳识别%正交局部保持投影
Log-Gabor濾波器%人耳識彆%正交跼部保持投影
Log-Gabor려파기%인이식별%정교국부보지투영
Log-Gabor filter%Human ear recognition%OLPP(orthogonal locality preserving projections)
针对人耳角度变化引起识别率下降的问题,提出一种结合Log-Gabor滤波和正交局部保持投影(OLPP)的人耳识别方法。首先采用Log-Gabor对图像进行滤波来提取多尺度多方向的人耳纹理特征;然后在局部保持投影的原始优化问题中增加正交约束条件,迭代计算出一组具有正交性最优映射向量,约简了丰富的Log-Gabor特征,并保留了人耳非线性流形子空间与距离有关的结构信息和重构样本;最后用最小欧氏距离分类器进行分类识别。对比相关的方法,该方法提高了姿态人耳的识别率。实验结果表明该方法能良好地表征姿态人耳,对角度变化具有很好的鲁棒性。
針對人耳角度變化引起識彆率下降的問題,提齣一種結閤Log-Gabor濾波和正交跼部保持投影(OLPP)的人耳識彆方法。首先採用Log-Gabor對圖像進行濾波來提取多呎度多方嚮的人耳紋理特徵;然後在跼部保持投影的原始優化問題中增加正交約束條件,迭代計算齣一組具有正交性最優映射嚮量,約簡瞭豐富的Log-Gabor特徵,併保留瞭人耳非線性流形子空間與距離有關的結構信息和重構樣本;最後用最小歐氏距離分類器進行分類識彆。對比相關的方法,該方法提高瞭姿態人耳的識彆率。實驗結果錶明該方法能良好地錶徵姿態人耳,對角度變化具有很好的魯棒性。
침대인이각도변화인기식별솔하강적문제,제출일충결합Log-Gabor려파화정교국부보지투영(OLPP)적인이식별방법。수선채용Log-Gabor대도상진행려파래제취다척도다방향적인이문리특정;연후재국부보지투영적원시우화문제중증가정교약속조건,질대계산출일조구유정교성최우영사향량,약간료봉부적Log-Gabor특정,병보류료인이비선성류형자공간여거리유관적결구신식화중구양본;최후용최소구씨거리분류기진행분류식별。대비상관적방법,해방법제고료자태인이적식별솔。실험결과표명해방법능량호지표정자태인이,대각도변화구유흔호적로봉성。
Aiming at the decline in recognition rate caused by the variation of human ear angle,we propose in this paper a novel ear recognition method which is based on Log-Gabor filter and orthogonal locality preserving projection (OLPP).First,the multi-scale and multi-orientation texture feature of ear image is extracted from the image using Log-Gabor filter.Then the orthogonal constraint conditions are added to the primitive optimisation problem in regard to locality preserving projection,and a set of projection vectors with orthogonal optimum is calculated through iteration.Abundant Log-Gabor features are reduced,and the structure information and reconstruction sample of nonlinear submanifold space of the ear related to distance are preserved.Finally,the minimum Euclidean distance classifier is applied in classification and recognition.In contrast to the correlated method,the proposed method improves the recognition rate of pose ear variation.Experimental result shows that this method can well represent multi-pose ear image,and is robust to the variation of ear angle.