International Journal of Electrical and Computer Engineering (IJECE) Vol. 14, No. 2, April 2024, pp. 1299∼1307 ISSN: 2088-8708, DOI: 10.11591/ijece.v14i2.pp1299-1307 ❒ 1299 Image enhancement in palmprint recognition: a novel approach for improved biometric authentication Muhammad Kusban, Aris Budiman, Bambang Hari Purwoto Department of Electrical Engineering, Faculty of Engineering, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia Article Info Article history: Received Nov 6, 2023 Revised Dec 3, 2023 Accepted Dec 13, 2023 Keywords: 3W filter image enhancement Cosine matching method Gabor orientation scale Kernel principal component analysis Palmprint recognition ABSTRACT Several researchers have used image enhancement methods to reduce detection errors and increase verification accuracy in palmprint identification. Divergent opinions exist among experts regarding the best method of image filtering to improve image palmprint recognition. Because of the unique characteristics of palmprints and the difficulties in preventing counterfeiting, image-filtering techniques are the subject of this current research. Researchers hope to cre- ate the best biometric system possible by utilizing various techniques. These techniques include image enhancement, Gabor orientation scales, dimension reduction techniques, and appropriate matching strategies. This study investi- gates how different filtering approaches might be combined to improve images. The palmprint identification system uses a 3W filter, which combines wavelet, Wiener, and weighted filters. Optimizing results entails coordinating the 3W filter with Gabor orientation scales, matching processes, and dimension reduc- tion methods. The research shows that accuracy may be considerably increased using a 3W filter with a Gabor orientation scale of [8 × 7], the kernel principal component analysis (KPCA) dimension reduction methodology, and a cosine matching method. Specifically, a value of 99.722% can be achieved. These re- sults highlight the importance of selecting appropriate settings and techniques for palmprint recognition systems. This is an open access article under the CC BY-SA license. Corresponding Author: Muhammad Kusban Department of Electrical Engineering, Universitas Muhammadiyah Surakarta A. Yani St., Trompol Pos 1 Pabelan, 57163, Surakarta, Indonesia Email: Muhammad.Kusban@ums.ac.id 1. INTRODUCTION Image enhancement is pivotal in boosting the accuracy and efficiency of biometric systems [1]. With more transparent images and sharper details, systems can identify and verify individual identities more quickly and accurately [2]. Moreover, enhanced images reduce the potential errors that might arise due to background disturbances or noise in the image [3]. In the rapidly evolving realm of biometrics, image enhancement has become a crucial technique [4]. The goal of image enhancement is to improve the visual and aesthetic quality of images and facilitate subsequent processing stages [5]. The world of image enhancement is filled with various methods, each tailored for a specific purpose [6]. Each technique has its advantages and challenges, depending on the nature of the image and the purpose of its processing [7]. For instance, a method suitable for medical images might not be suitable for satellite images [7]. Image enhancement is not a simple process but a complex journey involving various aspects and techniques [8]. In image processing, various dimensions are needed, ranging from adjusting color, contrast, and Journal homepage: http://ijece.iaescore.com