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The segmented blood vessel in retinal images is an important indicator in medical treatment. In 2007, Ricci and Perfetti proposed a simple and efficient blood vessel segmentation method based on line operator. However, this scheme makes some false segmentation when it is used to process the pixels which are close to a thick blood vessel. To overcome the above problem, a novel retinal blood vessel...
In this paper, we propose a classification mechanism for retinal images so that the retinal images can be successfully distinguished from nonretinal images, egg yolk images for example. The proposed classification mechanism consists of two procedures: training and classification. The image features of retinal images and nonretinal images are extracted at the beginning of the training procedure to...
Protecting data transmitted over the Internet has become a critical issue driven by the progress in data digitalization and communications networking over the past decade. The content being transmitted can be in the form of images, text and voice. To ensure that transmitted data are secure and cannot be tampered with or noticed by malicious attackers, several approaches have been proposed. Steganography...
Because smaller shadows can help speed up the transmission of a secret color image, in this paper we first modify the AMBTC, then combine our modified AMBTC and Shamir's (k, n) threshold scheme to propose a novel secret color image sharing scheme that generates smaller shadows. Experimental results confirm that the proposed scheme successfully reduces shadow size and that each shadow behaves as a...
In this paper, we propose a color-based segmentation method that uses the K-means clustering technique to track tumor objects in magnetic resonance (MR) brain images. The key concept in this color-based segmentation algorithm with K-means is to convert a given gray-level MR image into a color space image and then separate the position of tumor objects from other items of an MR image by using K-means...
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