IMAGE SEGMENTATION USING FUZZY LOGIC AND GENETIC
Department of
Computer Science, Sultan Qaboos University
P.O Box 36,
Al-Khod 123
Muscat, Oman
E--mail: muhamad@squ.edu.om
Genetic
algorithms (GAs) and fuzzy logic (FL) have been playing important roles in
solving many problems in pattern recognition and image
processing. This paper presents a hybrid approach of
GAs and FL that is used to fuse (combine) extracted features from intensity and
range images. GAs are used to help construct membership functions
that are necessary to classify the strength of existence of image features
through FL. Since range and intensity images provide different types of sensory
modality, fusing the extracted features from these images reveals more accurate
information about the scene . The extracted features are fused to generate a segmented image
of the scene. The
segmented image is compared with its ideal counterpart for the purpose of
experimental evaluation.
Keywords: Edge detection; Fusion systems; Fuzzy set;
GAs; Image segmentation.