Abstract
Thepurpose of this study is torealize image-understanding by computer.Image is consideredas an informational medium for human, and image-understanding is defined as the translation of the connotation of picture into natural language. A landscape, which is composed of natural things, is chosen as an example. This paper consists of three phases. In the first phase, a kind of elements are recognized by using fuzzy inference, because natural things which are constituent elements of landscape are so ・・ various in size, shape and color that ordinary method of pattern recognition is hardly applied. So, representing in advance the basic and general characteristics of elements in natural language should be considered. This representation is stored in date base in the form of fuzzy sets. On the other hand, the characteristics of the target image should be detected and represented by the form of fuzzy sets. By matching of the two, which images would enable qualitative comparisons of the characteristics, the recognition is facilitated. In the second phase, we analyze human behavior for image understanding by eye-motion cameraand also analyze how human expresses the image linguistically. According to experimental results, the flow-chart and the membership functions in words used in sentences are identified. In the third phase, the information processing of human is simulated by a computer, that is, the elements of image are represented by using information of contour. After that, the global meaning of the image is represented in a sentence automatically. These results are verified by experiment using some simple pictures of scenery.
