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

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.