Knowledge extraction from scenery images and the recognition using fuzzy inference neural networks

Hitoshi Iyatomi, Masafumi Hagiwara

Research output: Contribution to journalConference article

1 Citation (Scopus)

Abstract

A new system of knowledge extraction and recognition from scenery images is proposed in this paper. The system can extract different levels of knowledge automatically using Fuzzy Inference Neural Network (FINN). The proposed system consists of several Knowledge Extraction Networks (KENs). Each one is composed of FINN, and it can extract fuzzy if-then rules automatically. The KEN has an input-output (I/O) layer and two different-sized rule layers. The I/O layer includes the input part and the output part. The input part receives information on a pixel such as the position, the Intensity, the Hue and the Saturation. The output part receives the label of the corresponding pixel such as sky, mountains and woods, etc. The larger rule layer extracts detailed knowledge and it uses for the image recognition. On the other hand, the smaller rule layer extracts global knowledge which can correct contradiction of detailed knowledge and can remove trivial knowledge. It can be seen that the proposed system can recognize the image almost correctly by computer experiments. Knowledge is obtained by integrating rules from each KEN and then translating them into linguistic form. The extracted knowledge is quite natural.

Original languageEnglish
Pages (from-to)4486-4491
Number of pages6
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume5
Publication statusPublished - 1998 Dec 1
EventProceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics. Part 3 (of 5) - San Diego, CA, USA
Duration: 1998 Oct 111998 Oct 14

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture

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