Narrow Results

In this paper, we present a novel method to solve the inter-frame interpolation problem in image morphing. We use our improved snake model that is associated with the gravitational force field to locate control points in the object contours. Afterwards, we apply the greedy algorithm in free-form deformations to achieve optimal warps among feature point pairs in starting and ending frames. The new method uses an energy-minimization function under the influence of inter-frames. The energy serves to impose frame-wise and curve-wise constraints among the interpolated frames.

The process of retinal vessel segmentation is important for detection of various eye conditions including the effect of diabetes on eyes, or diabetic retinopathy. As we know, the retinal microvasculature is unique since it is the only part of the human circulation system that can be directly and non-evasively visualized in vivo; readily photographed as well as subjected to digital image analysis. This paper explores a new technique for detecting the idiosyncrasies of retina images, for which we have reviewed some well-known image segmentation algorithms that help in detecting retinal abnormalities. In this work, we have also focused on the extraction of the vessel from retina images and developed an automated diagnostic system for diabetic retinopathy. This paper represents techniques, such as the snake model that was used for auto-extraction of retinal blood vessels and use of wavelet decomposition and back propagation neural network to extract the retinal vessels features and analyze the dataset. Finally, an analysis of performance of the vessel segmentation algorithm and wavelet analysis on standard image databases has been done. In this context, we have used F-score for validation of the result.