计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2014年
5期
142-146
,共5页
人脸识别%典型相关分析%子模式%主成分分析
人臉識彆%典型相關分析%子模式%主成分分析
인검식별%전형상관분석%자모식%주성분분석
face recognition%canonical correlation analysis%sub-pattern%Principal Component Analysis(PCA)
为了提高人脸的识别率,提出一种典型相关分析融合全局和局部特征的人脸识别算法(SUB-CCA)。通过划分子模式方式避免人脸识别存在小样本、非线性问题,并提取局部特征,采用主成分分析提取人脸图像的全局特征,并采用相关分析算法对全局、局总特征进行融合,消除特征间冗余信息,降低特征维数,采用投票法得到人脸识别结果,并采用3个人脸数据集对算法性能进行测试。仿真结果表明,相对于参比算法,SUB-CCA提高了人脸识别的识别精度。
為瞭提高人臉的識彆率,提齣一種典型相關分析融閤全跼和跼部特徵的人臉識彆算法(SUB-CCA)。通過劃分子模式方式避免人臉識彆存在小樣本、非線性問題,併提取跼部特徵,採用主成分分析提取人臉圖像的全跼特徵,併採用相關分析算法對全跼、跼總特徵進行融閤,消除特徵間冗餘信息,降低特徵維數,採用投票法得到人臉識彆結果,併採用3箇人臉數據集對算法性能進行測試。倣真結果錶明,相對于參比算法,SUB-CCA提高瞭人臉識彆的識彆精度。
위료제고인검적식별솔,제출일충전형상관분석융합전국화국부특정적인검식별산법(SUB-CCA)。통과화분자모식방식피면인검식별존재소양본、비선성문제,병제취국부특정,채용주성분분석제취인검도상적전국특정,병채용상관분석산법대전국、국총특정진행융합,소제특정간용여신식,강저특정유수,채용투표법득도인검식별결과,병채용3개인검수거집대산법성능진행측시。방진결과표명,상대우삼비산법,SUB-CCA제고료인검식별적식별정도。
In order to improve the recognition rate of face image, a novel face recognition method is proposed based on sub-pattern and canonical correlation analysis. The global and local features are extracted, and the redundant information between the features is eliminated, and then the face images are divided in sub models to avoid small sample, nonlinear problems, and the recognition results are corrected by voting method to increase stability of the algorithm, three face data sets are used to test the performance of the algorithm. The simulation results show that, SUB-CCA improves the recogni-tion rate of face image compared with other algorithms.