Analyzing the Performance of Canny Edge Detection on Interpolated Images

Title

Analyzing the Performance of Canny Edge Detection on Interpolated Images

Creator

Kim Y.W.; Oh A.R.; Rose I.J.; Krishna A.V.N.

Description

Surveillance cameras are extensively used nowadays in many commercial and domestic places to monitor theft, intrusion and other illegal activities. Typically, the cameras are placed at a high position to monitor a large area. Therefore, the captured images include background area in addition to the target objects. Under such situation, the image can be zoomed to focus on the target objects using various interpolation techniques. For further processing of the image, many techniques like edge detection, image sampling and image thresholding etc. are available. Considering edge detection to be a basic step for many application such as Object detection, Object recognition etc, in this work, we analyze the performance of the Canny Edge Detection algorithm on images interpolated using Nearest Neighbour, Bilinear and Bicubic interpolation methods. Canny Edge Detection is applied to the input image and the resultant image is saved for later comparison. The same image is upscaled using interpolation and the Canny Edge Detection algorithm is used on this upscaled image. This image is then resized to the original image size. Both the images are compared to check for their similarity using the Structural Similarity Index Method (SSIM). 2019 IEEE.

Source

ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future, pp. 726-730.

Date

2019-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Bicubic Interpolation; Bilinear Interpolation; Canny Edge Detection; Nearest Neighbour Interpolation; Structural Similarity Index Method (SSIM).

Coverage

Kim Y.W., CHRIST Deemed to Be University, Centre for Digital Innovation, Bangalore, India; Oh A.R., ETRI, 218 Gajeong-ro, Yuseong-gu, Daejeon, South Korea; Rose I.J., CHRIST Deemed to Be University, Centre for Digital Innovation, Bangalore, India; Krishna A.V.N., CHRIST Deemed to Be University, Centre for Digital Innovation, Bangalore, India

Rights

Restricted Access

Relation

ISBN: 978-172810892-6

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICTC46691.2019.8939595

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078260549&doi=10.1109%2fICTC46691.2019.8939595&partnerID=40&md5=14cbbac87503708698410b22ad752a90