Gabor Filter and Rough Clustering Based Edge Detection
This is an incremental improvement for image processing applications, offering a soft computational approach to edge detection.
The paper tackles edge detection in images by combining Gabor filtering and rough clustering, resulting in a method that is shown to be effective through comparisons with other techniques, though no specific numerical gains are provided.
This paper introduces an efficient edge detection method based on Gabor filter and rough clustering. The input image is smoothed by Gabor function, and the concept of rough clustering is used to focus on edge detection with soft computational approach. Hysteresis thresholding is used to get the actual output, i.e. edges of the input image. To show the effectiveness, the proposed technique is compared with some other edge detection methods.