Title :
Notice of Retraction
Image fault area detection algorithm based on visual information integrate model
Author :
Peng Lu ; Eryan Chen ; Yuhe Tang ; Yongqiang Li ; Li Shi ; Qingyi Gao
Author_Institution :
Sch. of Electr. Eng., Zhengzhou Univ., Zhengzhou, China
Abstract :
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Space arrangement of basic functions of the natural scenes decomposed by basic ICA which simulates visual perception is chaotic. The result is contradicted with physiological mechanisms of vision. So, we put up with a new model to solve the problem which based on the information integrate mechanism in visual cortex receptive fields. And, to solve the problem of train image fault area detection, a novel algorithm is proposed by using this new model. Experimental results show that the new algorithm can increase fault detection rate with high efficiency and little samples compared with traditional methods which absence of the visual information integrate mechanisms.
Keywords :
independent component analysis; object detection; basic ICA; image fault area detection algorithm; natural scenes; visual cortex receptive fields; visual information integrate mechanisms; visual perception; Algorithm design and analysis; Brain modeling; Fault detection; Feature extraction; Neurons; Topology; Visualization; Visual information integrate; fault detection; neuronal response; topology basic functions;
Conference_Titel :
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9950-2
DOI :
10.1109/ICNC.2011.6022286
