A new recognition method for natural images

Authors:
Weiren Shi;Zuojin Li;Xin Shi;Zhi Zhong
Affiliations:
College of Automation, Chongqing University, Chongqing, People's Republic of China;College of Automation, Chongqing University, Chongqing, People's Republic of China;College of Automation, Chongqing University, Chongqing, People's Republic of China;The Smartech Institute, Shenzhen, People's Republic of China
Venue:
WSEAS Transactions on Computers
Year:
2009

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Abstract

Natural images recognition is an important area of machine vision. This paper presents a novel approach for natural images recognition, based on the non-Gaussian distribution property of natural images. In this new method for recognition, first supervised classification is conducted to the natural images based on their label value, then independent components linear transforms are conducted to each category of samples, high-dimensional data are transformed to irrelevant independent components, and finally the probability distance between independent component subspaces is used for unsupervised classification. This classification tree also shows some features of signal processing of biological optic nerve. Experiment on ORL Face Database identity recognition shows that this method is featuring high recognition rate and low time consumption; meanwhile, another experiment is conducted on direction determination of intelligent robots autonomous navigation, also producing a good result.