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Common Vector Approach Based Image Gradients Computation for Edge Detection

  • Sahin IsikEmail author
  • Kemal Ozkan
Conference paper
  • 32 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11989)

Abstract

In this study, the concept of Common Vector Approach (CVA) is adopted for image gradients computation in terms of revealing edge maps stated on images. Firstly, noise stated on image is smoothed by Gaussian filtering, secondly gradient map computation using CVA is carried out, then the angle and direction maps are obtained from the gradient map and lastly peak points are selected and a smart routing procedure is performed to linking them. With an unusual methodology, the derivatives of image through vertical and horizontal directions have obtained by utilizing the CVA, which is the crucial step and gained the novelty to this work. To compare results objectively, we have judged the performance with respect to a comparison metric called ROC Curve analysis. As a contribution to the edge detection area, CVA-ED presents satisfactory results and edge maps produced can be used in the tasks of object tracking, motion estimation and image retrieval.

Keywords

Edge detector Common vector approach Edge gradient map 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Computer Engineering DepartmentEskisehir Osmangazi UniversityEskişehirTurkey

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