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An application of the theory of fuzzy sets in understanding an image is demonstrated. The task of understanding consists of three parts. A representation of image contours by their respective chains of octal codes, smoothing of the chain to remove spurious wiggles, and segmentation and assignment of degree of `arcness' to each segmented smoothed chain in order to extract their primitives for description. Octal code is provided to a two-pixel or, even more length contour by taking maximum of its grades of membership corresponding to `vertical', `horizontal' and `oblique' lines. Four different smoothers have been used to eliminate the spurious wiggles occurring in the contours. Segmentation of edges into different curves and lines is made on the basis of constant change in code values. The primitives for description and interpretation of images are extracted by assigning the appropriate membership value which provides a measure of curvature to the different arcs. The sense of curving is also determined. The effectiveness of the algorithm is demonstrated when a gray tone edge-detected X-ray image of wrist is considered as input.