Title :
Application of Neural Networks in Image Definition Recognition
Author :
Guojin, Chen ; Miaofen, Zhu ; Honghao, Yu ; Yan, Li
Author_Institution :
Hangzhou Dianzi Univ., Hangzhou, China
Abstract :
To simulate the auto-focus mechanism of human´s eyes by using artificial neural networks is a reasonable and available way to improve the auto-focus effect of digital cameras. The evaluation of image definition plays a key role in the auto-focus of digital cameras, so constructing the image definition evaluation is an important step of designing auto-focus systems. In this paper, we use the pattern recognition method of the RBF neural networks to recognize the image definition. The designed neural networks are trained by the training set that is composed of 75 pictures. Then, the testing set that is composed of 102 pictures is verified experimentally. The experiment results indicate that this method is quite effective. The method gives full play to self-adapting ability of neural networks and gets a higher recognition rate.
Keywords :
cameras; image recognition; learning (artificial intelligence); optical focusing; radial basis function networks; RBF neural networks; artificial neural networks; auto-focus effect; auto-focus mechanism; auto-focus systems; digital cameras; human eyes; image definition evaluation; image definition recognition; neural networks training; pattern recognition method; self-adapting ability; Artificial neural networks; Biomedical optical imaging; Digital cameras; Eyes; Focusing; Humans; Image recognition; Neural networks; Pattern recognition; Retina; Neural networks; image processing; pattern recognition;
Conference_Titel :
Signal Processing and Communications, 2007. ICSPC 2007. IEEE International Conference on
Conference_Location :
Dubai
Print_ISBN :
978-1-4244-1235-8
Electronic_ISBN :
978-1-4244-1236-5
DOI :
10.1109/ICSPC.2007.4728542
