Open Access

ARTICLE

Hybrid Optimization Algorithm for Handwritten Document Enhancement

Shu-Chuan Chu¹, Xiaomeng Yang¹, Li Zhang², Václav Snášel³, Jeng-Shyang Pan^1,4,*

1 College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China
2 School of Information and Control Engineering, Qingdao University of Technology, Qingdao, 266520, China
3 Faculty of Electrical Engineering and Computer Science, VŠB-TU Ostrava, Ostrava, 70080, Czech Republic
4 Department of Information Management, Chaoyang University of Technology, Taichung, 41349, Taiwan

* Corresponding Author: Jeng-Shyang Pan. Email:

(This article belongs to the Special Issue: Metaheuristics, Soft Computing, and Machine Learning in Image Processing and Computer Vision)

Computers, Materials & Continua 2024, 78(3), 3763-3786. https://doi.org/10.32604/cmc.2024.048594

Received 12 December 2023; Accepted 24 January 2024; Issue published 26 March 2024

Abstract

The Gannet Optimization Algorithm (GOA) and the Whale Optimization Algorithm (WOA) demonstrate strong performance; however, there remains room for improvement in convergence and practical applications. This study introduces a hybrid optimization algorithm, named the adaptive inertia weight whale optimization algorithm and gannet optimization algorithm (AIWGOA), which addresses challenges in enhancing handwritten documents. The hybrid strategy integrates the strengths of both algorithms, significantly enhancing their capabilities, whereas the adaptive parameter strategy mitigates the need for manual parameter setting. By amalgamating the hybrid strategy and parameter-adaptive approach, the Gannet Optimization Algorithm was refined to yield the AIWGOA. Through a performance analysis of the CEC2013 benchmark, the AIWGOA demonstrates notable advantages across various metrics. Subsequently, an evaluation index was employed to assess the enhanced handwritten documents and images, affirming the superior practical application of the AIWGOA compared with other algorithms.

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Keywords

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