基于主独立内容特征的人脸图像检索方法

提出一种基于独立分量分析的内容特征，并用于人脸图像检索，得到一种基于内容的图像检索新方案.该方案首先在降维空间提取出基于高阶统计特性的主独立内容特征(PICF)，应用提取的PICF特征进行有效的人脸图像描述.为确保计算有效性和检索正确率，运用可消除独立特征顺序不确定性的基于PICF的检索方法，并在具备不同亮度、尺度、姿势和图像描述变化的ORL脸谱数据库中完成了人脸图像检索实验.计算机仿真结果验证了所提出方法的有效性.最佳检索率为100%，平均查准率达95.14％/千次.

Research on face image retrieval based on principal independent content features

In this paper, a novel kind of content feature is proposed to be extracted by independent component analysis (ICA) and used for face image retrieval. A novel content-based face image retrieval scheme is created based on this content feature—principle independent content feature (PICF). In this scheme, PICF based on higher order statistics is first extracted in the reduced space for effective representation of face images. To ensure the efficiency of computation and accuracy of retrieval, a PICF-based retrieval method that can eliminate the ambiguity in the order of independent features is used in the face image retrieval stage with the ORL database, where the images vary in illumination, expression, pose, and scale. The simulation proves the feasibility of the proposed PICF-based method and the highest  accuracy can reach 100%, and  the average precision  reaches 95.14% per thousand experiments in our simulations.