CAJ | 학술논문

本文提出了一种新型的表情组合模板与Gabor小波相结合的面部表情识别方法.借助Gabor小波变换在图像处理领域的优势,克服不同因素给表情识别带来的不利影响,有效的提取与表情变化有关的特征,从分类的角度来构造的表情组合模板.在人脸检测的基础上,利用Gabor小波变换提取各个区域的特征矢量,与待识别表情对应的各个特征区域的特征矢量进行比较,利用欧氏距离选择最小值对应的矢量,返回表情组合模板中,确定待识别表情的类型.实验表明该方法的识别率可达83%,表情识别效果较好.
본문제출료일충신형적표정조합모판여Gabor소파상결합적면부표정식별방법.차조Gabor소파변환재도상처리영역적우세,극복불동인소급표정식별대래적불리영향,유효적제취여표정변화유관적특정,종분류적각도래구조적표정조합모판.재인검검측적기출상,이용Gabor소파변환제취각개구역적특정시량,여대식별표정대응적각개특정구역적특정시량진행비교,이용구씨거리선택최소치대응적시량,반회표정조합모판중,학정대식별표정적류형.실험표명해방법적식별솔가체83%,표정식별효과교호.
This paper presents a new method of face recognition, with a combination of facial expression templates and Gabor wavelet. With the aid of Gabor wavelet transformation in the field of image processing, the method discussed could effectively extract charac-teristics of facial expression, overcome the negative impacts of individual differences as well as construct expression templates from the perspective of the classification. First, on the basis of face detection, we use of Gabor wavelet transformation to extract vector in each area. Then compares feature vectors of expression to be recognized in each feature area. After choosing the vector corresponding to the minimum by using Euclidean distance, it will turn back to the expression combination template and finally identify the type of expression. Experiments show that the identification rate of method is as high as 83% and the effect of expression identification is ex-cellent.