PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Montanari U. Optimization methods in Image Processing. In: Information processing 74 : proceedings of IFIP congress 74, Stockholm, Sweden, August 5-10, 1974., pp. 727 - 732. Jack L. Rosenfeld (editor). North-Holland, 1974.
 
 
Abstract
(English)
In most cases, picture recognition requires precisely tuned procedures. Furthermore, small changes in the involved heuristics often imply extensive reprogramming. Optimization methods specify an easy-to-change figure of merit, which gives the best values to "perfect" objects and expresses how to penalize defects. Standard optimization procedures are then applied to find an optimal object in the given picture. These techniques have been applied in both the preprocessing (line and contour detection, smoothing) and the recognition phase (human faces, terrain scenes, lung and liver cancer). Optimization methods compare favourably in performance with other techniques since they are intrinsically global, while approximate implementations have been developed to shorten computing time. An interesting feature of such experiments is that time and storage requirements are a function of image quality.
Subject Image processing


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