• Mugdha Thareja
• Pratibha

ABSTRACT Digital Image Processing is a efficient approach of changing an image with finite number of elements that possess a particular vector element known as pixels. It involves a series of sequential steps adjusting with the acquisition of image and terminating at the identification of target object. The inspiration behind this research work centers on the increasing use of image segmentation techniques in different sectors of various industrial domains. This dissertation work has been feature detection methods viz. Canny, Sobel, Harris, SUSAN and Laplace. A comparison was compiled based on the observations after introducing variations in the related parameters like Performance Ratio (PR), Signal to Noise Ratio, Peak Signal carried out in the form of performance analysis of well-known to Noise Ratio (PSNR) and Threshold Value (TV).

Image Segmentation, computer vision system, feature detection algorithms, edge detection, image corner detection

"Comparative Performance Analysis of Feature Detection Algorithms ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.26-33, July-2018, Available :http://www.jetir.org/papers/JETIR1807003.pdf

"Comparative Performance Analysis of Feature Detection Algorithms ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp26-33, July-2018, Available at : http://www.jetir.org/papers/JETIR1807003.pdf