This paper presents the results of experiments on the automatic recognition of few-pixel images in comparison with the data of visual recognition. The automatic recognition of few-pixel images is accomplished by means of an adaptive algorithm based on a compact description of the objects of an alphabet in the form of functional dependences of the mean values of the shape attributes and their rms deviations on the size of the image of an object and by using a fuzzy deciding rule with computation of confidence measures to hypotheses concerning the relation of the object to be recognized, applied to one of the objects of the alphabet. It is shown that applying an interpolation procedure to few-pixel images significantly increases the operating efficiency of the adaptive algorithm.
P. A. Medennikov and N. I. Pavlov, "Visual and automatic recognition of objects from few-pixel images," J. Opt. Technol. 70, 101-104 (2003)
References are not available for this paper.
|Alert me when this paper is cited|
OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.