Current Science

Sajid Khan ¹, Dong-Ho Lee ², Muhammad Asif Khan ³, Abdul Rehman Gilal ⁴, Junaid Iqbal ⁵, Ahmad Waqas ⁴

Affiliations
1 Center of Excellence for Robotics, Artificial Intelligence and Blockchain, Sukkur IBA University, Sukkur, PK
2 School of Electrical Engineering, Hanyang University ERICA Campus, Ansan, KP
3 Department of Electrical Engineering, Sukkur IBA University, Sukkur, PK
4 Department of Computer Science, Sukkur IBA University, Sukkur, PK
5 Department of Mechatronics Engineering, Hanyang University ERICA Campus, Ansan, KP

Abstract

Hysteresis thresholding is a popular technique for automatic edge detection. However, calculating reasonably high and low thresholds using an unsupervized method remains an issue. Conventional low and high threshold-linking methods sometimes produce noisy edges and fail to detect some obvious edges. Here, a novel edge detection algorithm is proposed that provides efficient calculation of thresholds, and links edge maps for extraction of the final edge map at low complexity. The proposed method suppresses unwanted noisy edges while efficiently preserving obvious edges. The simulation results show that the proposed method provides better results in terms of performance and computation time. Thus, it can be applied to any feature imageanalysed by an edge detector.

Keywords

Edge Detection, Hysteresis Method, Low and High Thresholds, Noise Suppression.

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