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A Survey on Different Edge Detection Techniques for Image Segmentation


Affiliations
1 Department of ISE, Sri Venkateshwara College of Engineering, Bengaluru - 562157, Karnataka, India
 

Objectives: To compare different edge detection techniques for the effective performance results with respect to complex images. Methods: This paper compares and analyses the performance of diverse edge detection techniques for recent digital image processing like canny optimal edge detection, sobel operator, prewitt operator and LoG. Findings: Canny Optimal Edge detection (COE) technique provides better performance results under noise images or complex images when compared to other techniques. In COE the result of PSNR is high which helps to identify the effective edges.

Keywords

Canny edge detection, Classical Operator Edge detection, Edge detection algorithm, Image segmentation.
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  • A Survey on Different Edge Detection Techniques for Image Segmentation

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Authors

K. Bala Krishnan
Department of ISE, Sri Venkateshwara College of Engineering, Bengaluru - 562157, Karnataka, India
Shiva Prakash Ranga
Department of ISE, Sri Venkateshwara College of Engineering, Bengaluru - 562157, Karnataka, India
Nageswara Guptha
Department of ISE, Sri Venkateshwara College of Engineering, Bengaluru - 562157, Karnataka, India

Abstract


Objectives: To compare different edge detection techniques for the effective performance results with respect to complex images. Methods: This paper compares and analyses the performance of diverse edge detection techniques for recent digital image processing like canny optimal edge detection, sobel operator, prewitt operator and LoG. Findings: Canny Optimal Edge detection (COE) technique provides better performance results under noise images or complex images when compared to other techniques. In COE the result of PSNR is high which helps to identify the effective edges.

Keywords


Canny edge detection, Classical Operator Edge detection, Edge detection algorithm, Image segmentation.



DOI: https://doi.org/10.17485/ijst%2F2017%2Fv10i4%2F139331