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Efficient Case Study for Image Edge Gradient Based Detectors - Sobel, Robert Cross, Prewitt and Canny

B. RAMESH NAIDU; Prof. M. S. PRASAD BABU; P. LAKSHMAN RAO; K. V. L. BHAVANI
In this paper we focused on the image processing techniques mainly Image enhancement and Feature extraction. Image enhancement is one of the most important issues in low-level image processing. Contrast enhancement (CE) is used widely in image processing. We implement one of the most popular CE methods called histogram equalization (HE). The HE uses the cumulative distribution function (CDF) of a given image as a mapping from the given image to the enhanced image; enhanced image follows the uniform distribution of histogram over the dynamic range of all intensities. It is a widely used contrast enhancement method in a variety of applications due to its simple function and effectiveness. Edges are important features in an image since they represent significant local intensity changes. They provide important clues to separate regions within an object. Edge detection on an image significantly reduces the amount of data and filters out useless information, while preserving the important structural properties in an image. We implemented edge Gradient based detectors- Sobel, Robert Cross, Prewitt and also Canny edge detector.
Select Volume / Issues:
Year:
2012
Type of Publication:
Article
Keywords:
Image Processing; Contrast enhancement; histogram equalization; cumulative distribution function; edge Gradient based detectors
Journal:
IJECCE
Volume:
3
Number:
3
Pages:
561-571
Month:
May
Hits: 1517

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