In the context if image indexing for the purpose of retrieval, colored object recognition methods tend to fail when the illumination of the objects varies from an image to another. A new approach to indexing image of persons is proposed, which copes with the variations of the lighting conditions. We assume that illumination changes can be described using a simple linear transform. For comparing two images, we transform the color of the target one according to the colors of the query one by means of an original color histogram specification based on color invariant evaluation. For the retrieval purpose, we evaluate invariant color signatures of the query image and the transformed target image through the use of color co-occurrence matrices. Tests on real images are very encouraging, with substantially better results than those obtained with other well--established indexing and retrieval schmes.
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A recursive edge tracking of the retinal blood vessel is presented in order to achieve a bidimensionnal reconstruction of the rential vasculature. First, color edge detection is applied on the original angiographic images. Second, from interactive selection of starting points near the papilla, the tracking of the two contours of a vessel is processed. The algorithm validates the next connected pixels to the current ones which satisfy the tracking hypotheses. Problems induced by the curvature of the vessel and the discontinuity of the detected edges will be dealed with. Third, during the tracking procedure is then performed from these branch points until the end of the vessel is reached. Contour and the color of the vessel's body are associated in order to get more accurate extraction. The reconstructed vacular strucures will be used as landmarks for the follow--up of a new retinopathy called CytoMegalo Virus retinitis found on patients with acquired immune deficiency syndrome (AIDS).
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