An Efficient Low Complex-Functional Link Artificial Neural Network-Based Framework for Uneven Light Image Thresholding-Reference-Cited by-同舟云学术

An Efficient Low Complex-Functional Link Artificial Neural Network-Based Framework for Uneven Light Image Thresholding

Published:2024 Issue: Volume:12 Page:118315-118338
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Pattnaik Tapaswini¹,Kanungo Priyadarshi²,Sahoo Prabodh Kumar³^ORCID,Kar Tejaswini⁴^ORCID,Jain Prince³^ORCID,Soliman Mohamed S.⁵^ORCID,Islam Mohammad Tariqul⁶^ORCID

Affiliation:

1. Department of Electronics and Telecommunication Engineering, Biju Patnaik University of Technology, Rourkela, Odisha, India

2. Department of Electronics and Telecommunication Engineering, Driems University, Tangi, Cuttack, Odisha, India

3. Department of Mechatronics Engineering, Parul Institute of Technology, Parul University, Vadodara, Gujarat, India

4. School of Electronics Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India

5. Department of Electrical Engineering, College of Engineering, Taif University, Taif, Saudi Arabia

6. Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, UKM, Bangi, Selangor, Malaysia

Funder

Universiti Kebangsaan Malaysia Research Grant through the Dana Padanan Kolaborasi

Taif University, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10643505.pdf?arnumber=10643505

Reference37 articles.

1. A Threshold Selection Method from Gray-Level Histograms

2. A New Iterative Triclass Thresholding Technique in Image Segmentation

3. A robust 2D Otsu’s thresholding method in image segmentation

4. Fast segmentation algorithm of PCB image using 2D OTSU improved by adaptive genetic algorithm and integral image

5. Robust 2D Otsu’s Algorithm for Uneven Illumination Image Segmentation