期刊
INFORMATION SCIENCES
卷 180, 期 16, 页码 2915-2924出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2010.04.021
关键词
Pixelared image; Visual prostheses; Low resolution; Recognition; Simulated prosthetic vision
资金
- National High Technology Research and Development Program of China (863 Program) [2009AA04Z326]
- The National Basic Research Program of China (973 Program) [2005CB724302, 2005CB724303]
- The National Natural Science Foundation of China [60671059, 60871091, 60971102]
- The National Key Technology RD Program [2007BAK27B04, 2008BAI65B03]
- Ministry of Education of China [B08020]
Visual prostheses based on micro-electronic technologies and biomedical engineering have been demonstrated to restore vision to blind individuals. It is necessary to determine the minimum requirements to achieve useful artificial vision for image recognition. To find the primary factors in common object and scene images recognition and optimize the recognition accuracy on low resolution images using image processing strategies, we investigate the effects of two kinds of image processing methods, two common shapes of pixels (square and circular) and six resolutions (8 x 8, 16 x 16, 24 x 24, 32 x 32, 48 x 48 and 64 x 64). The results showed that the mean recognition accuracy increased with the number of pixels. The recognition threshold for objects was within the interval of 16 x 16 to 24 x 24 pixels. For simple scenes, it was between 32 x 32 and 48 x 48 pixels. Near the threshold of recognition, different image modes had great impact on recognition accuracy. The images with threshold pixel number and binarization-circular points produced the best recognition results. (C) 2010 Elsevier Inc. All rights reserved.
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