Part Recognition Based on Maximum Mutual Information
A new approach to the problem of part recognition is proposed by using maximum mutual information. The method applies entropy to measure image feature, combined with color information and local shape information, and uses mutual information as a new matching criterion between the images for image recognition. This method solves the problem that histogram algorithm can not represent the spatial information. This method not only has the feature of translation invariant, but also avoids image segmentation which may lead to a complex calculation, so it can be realized easily. The result shows that proposed approach is accuracy, stability, and reliability in the processing of machine part image recognition.
Fan Rui, Qiao Lihong, Chen Huawei, Ochi Akio, Usuki Hiroshi and Sekiya Katsuhiko
S. Ge and D. G. Huang, "Part Recognition Based on Maximum Mutual Information", Key Engineering Materials, Vols. 407-408, pp. 234-238, 2009