Year: 1993
Type: article
Abstract: This paper describes a new technology on image recognition of objects using fuzzy theory. The standard method of pattern recognition is geometrical pattern matching. This is accomplished by comparing an object with a standard pattern, which is effective in cases having little ambiguity, such as industrial products. However, it is generally difficult to recognize natural products, because these objects have essential fuzziness caused by the differences is shapes, sizes and colors. In this paper, pictorial pattern recognition including these kinds of fuzziness is investigated, and a new image recognition system is proposed with the application of fuzzy theory. Through discrimination experiments made for ten categories such as apples, bannas, lemonns and others, satisfactory results are obtained. At result, it is certified that the pattern recognition proposed here is more effective to recognition of resemble objects categories.
Authors: Toshiyuki Asakura, Atsushi Ueda, Makoto Hizume
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W2326882255