An assembled matrix distance metric for 2DPCA-based image recognition

作者：Zuo WM; Zhang D^*; Wang KQ

来源：Pattern Recognition Letters, 2006, 27(3): 210-216.

DOI：10.1016/j.patrec.2005.08.017

• PCA
• 2DPCA
• image recognition
• face recognition
• palmprint recognition
• feature extraction

Two-dimensional principal component analysis (2DPCA) is a novel image representation approach recently developed for image recognition. One characteristic of 2DPCA is that it can extract feature matrix using a straightforward image projection technique. In this. paper, we propose an assembled matrix distance metric (AMD) to measure the distance between two feature matrices. To test the efficiency of the proposed distance measure, we use two image databases, the ORL face database and the PolyU palmprint database. The results of our experiments show that the assembled matrix distance metric is very effective in 2DPCA-based image recognition.

• 出版日期2006-2
• 单位香港理工大学; 哈尔滨工业大学