IMAGE SEGMENTATION AND RECOGNITION BY TEXTURE DISCRIMINATION: A SYNTACTIC APPROACH.

Problems arising from real world texture discrimination using syntactic approaches, such as texture orientation, selection of window sizes, and texture gray levels, thresholding, and primitive selection, etc. , are studied, and techniques and algorithms, such as direction detectors, rotational grammars, optimum window size inferrence algorithms, least-square-error structure-preserved error-correcting tree automata, and a random field approach to primitive selection, are proposed to solve these problems. These techniques are then applied to the segmentation and recognition of agricultural area pictures which are abundant with textures, and suggestions for further research are made in the concluding remarks.