CAJ | 학술논문

为解决人脸识别过程中出现的无法有效区分多姿态人脸的问题，进一步提高人脸表情识别率。本文在分析现有人脸表情识别方法的基础上，提出新的识别技术，即采用基于径向基函数（RBF）神经网络的方法，首先对图像皮肤和非皮肤像素进行分离，把人脸区域从检测到的皮肤区域中提取出来，然后以人脸表情数据库JAFFE为测试数据库，对人脸图像进行Gabor小波变换（GWT）和离散余弦变换（DCT），最后将该算法用于径向基函数神经网络的训练过程，建立相应优化模型，并将其应用到人脸表情的识别中，研究结果表明，具有收敛速度快、识别率高等优点，比文献中的方法提高了3%和8%的识别率。
위해결인검식별과정중출현적무법유효구분다자태인검적문제，진일보제고인검표정식별솔。본문재분석현유인검표정식별방법적기출상，제출신적식별기술，즉채용기우경향기함수（RBF）신경망락적방법，수선대도상피부화비피부상소진행분리，파인검구역종검측도적피부구역중제취출래，연후이인검표정수거고JAFFE위측시수거고，대인검도상진행Gabor소파변환（GWT）화리산여현변환（DCT），최후장해산법용우경향기함수신경망락적훈련과정，건립상응우화모형，병장기응용도인검표정적식별중，연구결과표명，구유수렴속도쾌、식별솔고등우점，비문헌중적방법제고료3%화8%적식별솔。
During face recognition,there exists a serious problem that it is very difficult to distinguish faces of various gestures. On the basis of the analysis of the existing facial expression recognition methods, this paper proposes a new recognition technology,skin and non-skin pixels were separated.RBF neural network is enrolled to recognize various faces.Face regions were extracted from the detected skin regions.Facial expressions are analyzed from facial mages by applying Gabor wavelet transform (GWT) and Discrete Cosine Transform (DCT) on face images.Finally applied the new algorithm to the problem of expression recognition.The results show that,this method has fast convergence speed,high recognition rate,than the methods in literatures to improve the recognition rate of 3% and 8%.