A retinal image has blood vessels, optic disc, fovea, and so forth as the main components of an image. Segmentation of these components has been investigated extensively. Principal component analysis (PCA) is one of the techniques that have been applied to segment the optic disc, but only a limited work has been reported. To our knowledge, fovea segmentation problem has not been reported in the literature using PCA. In this paper, we are presenting the segmentation of optic disc and fovea using PCA. The PCA was trained on optic discs and foveae using ten retinal images and then applied on seventy retinal images with a success rate of 97% in case of optic discs and 94.3% in case of fovea. Conventional algorithms feed one patch at a time from a test retinal image, and the next patch separated by one pixel part is fed. This process is continued till the full image area is covered. This is time consuming. We are suggesting techniques to cut down the processing time with the help of binary vessel tree of a given test image. Results are presented to validate our idea. 1. Introduction This paper presents an extension of the application of principal component analysis (PCA) to retinal images. Localization cases of optic disc and fovea have been presented in the literature [1–16] using techniques other than PCA except the optic disc localization by PCA which is discussed in [2]. In this paper, application of PCA is presented for two different cases: to automatically locate the position of the optic disc in a retinal image, and to automatically locate the position of the fovea in a retinal image. To our knowledge, the latter application is novel and has not been reported in the literature. The former application has been discussed in the literature [2]. The information contained in [2] does not fully appreciate the scope of PCA in optic disc localization. This paper will elaborate the work of optic disc localization and will extend the scope of this work to the localization of fovea. The algorithm we have developed for the localization of optic disc and fovea works faster than the one reported in [2]. The application of PCA to determine the location of the fovea is a relatively difficult problem as compared with locating the optic disc because the fovea usually has lower contrast compared with the optic disc in a retinal image. Knowledge of the optic disc location and its diameter is important in the automatic analysis of retinal images. A variety of techniques to automatically determine the location of the optic disc in a retinal image have been described in the
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