EDGE DETECTION IN IMAGES

Noisy images edge detection: Ant colony optimization algorithm

The edges of an image define the image boundary. When the image is noisy, it does not become easy to identify the edges. Therefore, a method requests to be developed that can identify edges clearly in a noisy image. Many methods have been proposed earlier using filters, transforms and wavelets with Ant colony optimization (ACO) that detect edges. We here used ACO for edge detection of noisy ima...

Edge detection in multispectral images

Edge Detection in Brain Images

In this paper problem of edge detection in digital images is considered. Particular attention is paid to brain magnetic resonance images. The new approach to edge detection is introduced. Results of proposed method are presented and compared with traditional approach. In this work, a new contour detection method is studied for detecting brain tumor regions based on their gradient magnitude info...

Edge Detection in Multispectral Images

This paper proposes an extension of edge detectors based on second-order differential operators to the case of multiple band (color) images. To this end, we deline a local directional measure of multispectral contrast. A definition of edge point is then given, as the location of a directional maximum of the contrast function. Extremal contrast edges are defined, as loci of zero crossing points ...

Edge Detection in Low Contrast Images

Abstract—The edges of low contrast images are not clearly distinguishable to human eye. It is difficult to find the edges and boundaries in it. The present work encompasses a new approach for low contrast images. The Chebyshev polynomial based fractional order filter has been used for filtering operation on an image. The preprocessing has been performed by this filter on the input image. Laplac...