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This paper presents a new approach to retrieve images by content using a composition of relevant features regarding texture, shape and brightness distribution. The first step of the method is a segmentation process based on Markov random fields, which can be done automatically, having as parameter the number of desired classes. The regions obtained in the segmentation guide the extraction of measures from the original image producing a 30-dimensional feature vector used in the image retrieval. The experiments showed that the feature vector has high discrimination power and the time for retrieval operations are only fractions of seconds.