Color character recognition method based on a model of human visual processing

Kazuo Yamaba; Yoichi Miyake

doi:10.1117/12.44364

1 June 1991 Color character recognition method based on a model of human visual processing

Kazuo Yamaba, Yoichi Miyake

Proceedings Volume 1453, Human Vision, Visual Processing, and Digital Display II; (1991) https://doi.org/10.1117/12.44364
Event: Electronic Imaging '91, 1991, San Jose, CA, United States

Abstract

Color is one of the most important types of visual information in various environmental conditions such as space, underwater and so on. This area of study, however, is still a young technology. In particular, the use of color vision in a color bar-code detecting system is a new area. On the other hand, neural net models have been studied for many years in the hope of achieving human-like performance. This paper deals with a color character recognition method based on a model of human visual processing. To realize a higher level of color character recognition, a new apparatus is constructed. The apparatus mainly consists of a color CCD camera corresponding to human eye, an image board, a neuro board and a microcomputer. In this experiment, ten characters are selected from a normal typewriter, and five kinds of colors are used as color characters and background colors under the illumination of a fluorescent lamp. The neuro board consists of an image pipe line processor and its network has three hierarchical structures using a back-propagation method. The experiment is carried out by employing models of human visual processing. The results show that it can recognize characters and colors at the same time.

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Kazuo Yamaba and Yoichi Miyake "Color character recognition method based on a model of human visual processing", Proc. SPIE 1453, Human Vision, Visual Processing, and Digital Display II, (1 June 1991); https://doi.org/10.1117/12.44364

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KEYWORDS

Optical character recognition

Visual process modeling

Visualization

Image processing

CCD cameras

Human vision and color perception

Neural networks

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