A functional enhancement on scarred fingerprint using sigmoid filtering

Neural Computing and Applications https://doi.org/10.1007/s00521-022-07520-x (0123456789().,-volV)(0123456789().,-volV) ORIGINAL ARTICLE A functional enhancement on scarred fingerprint using sigmoid filtering Hoshang Kolivand1,2,3 • Ainul Azura Binti Abdul Hamid3,4 • Shiva Asadianfam5,6 • Mohd Shafry Mohd Rahim3,4 Received: 13 September 2021 / Accepted: 7 June 2022  The Author(s) 2022 Abstract Fingerprint has been widely used in biometric applications. Numerous established researches on image enhancement techniques have been done to improve the quality of fingerprint images. However, the production of low-quality images due to the presence of scars remains a challenge in biometrics. The scars damage the fingerprint minutiae information due to broken ridges and they reduce the accuracy of identification. This research developed an image enhancement approach to improve the quality of scarred fingerprint images to generate accurate minutiae extraction. To achieve the aim, the scarred image was improved by removing noise using a new filter, Median Sigmoid (MS), and the corrected ridges were reconstructed using ridges structure enhancement algorithm. This was done to enhance the broken ridges structure. MS filter is a combination of median filter and modified sigmoid function that improves the image contrast and simultaneously removes noise in the fingerprint image. Following that, the filtered image was used in the ridges structure enhancement process. To identify true minutiae, the broken ridges structure in the filtered image needed to be accurately verified. In the ridges structure reconstruction process, an algorithm was enhanced to identify the best value of Sigma parameter (r) used in the Gaussian Low-pass filter to generate a better orientation image. The image is important to reconstruct the corrupted fingerprint ridges structure. The evaluation for the proposed approach used the National Institute of Standards and Technology Special Database 14, and the results showed a 37% improvement of the quality index in comparison to approaches found in related research. The findings of the evaluation showed that the proposed enhancement approach produced a better minutiae extraction result and this is very significant in the field of fingerprint image enhancement. Keywords Scarred fingerprint  Image processing  Median sigmoid filtering  Images enhancement  Biometric applications 1 Introduction & Hoshang Kolivand 1 Department of Computer Science, Liverpool John Moores University, Liverpool L3 3AF, UK 2 School of Computing and Digital Technologies, Staffordshire University, Stoke-on-Trent, UK 3 Media and Game Innovation Centre of Excellence, Institute of Human Centered Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia 4 School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia 5 Faculty of Electrical and Computer Engineering, Qom University of Technology, Qom, Iran 6 Department of Computer Engineering, Qom Branch, Islamic Azad University, Qom, Iran Biometrics is an accepted and dependable answer to solve the identity verification dilemma by identifying individuals based on the physiological or behavioral traits that are inherent to the person [5]. Physiological and behavioral traits that are normally utilized for biometric recognition are the face, fingerprint, iris, retina, DNA, signature, palm print, ear, voice, keystroke dynamics, hand geometry, and gait. Automated Fingerprint Identification System (AFIS) is recognized and acknowledged mostly by the whole world [18]. It is moreover turned out to be one of the significances in the security field that numerous researchers have attended to persist in carrying out research on it. The quality of the fingerprint image is essential to ensure the good performance of fingerprint recognition since the recognition process depends heavily on the quality of 123 Neural Computing and Applications fingerprint images [6]. A good quality fingerprint image has high contrast and is well defined by ridge structures. The poor quality of the fingerprint image is marked by low contrast and does not have well-defined boundaries between the ridges [22]. By having a good quality of fingerprint images as input to an automated fingerprint recognition system, the result is more accurate. However, in many previous works existed,it was proved that poor quality of fingerprint images will affect the accuracy of fingerprint recognition results [23, 29]. The performance of a minutiae extraction algorithm relies heavily on the quality of the input fingerprint images. A scarred fingerprint tends to change and damage the structure of the fingerprint ridges and valleys. This circumstance will result in an unreliable minutiae extraction and affects the accuracy of the fingerprint recognition. This research is conducted to remove the scar by choosing the right broken ridges that need to be reconnected. This reconnection process is made to improve the structure of the broken ridges so that the quality of the fingerprint images can be enhanced. So, the true minutiae could be extracted. The hypothesis for this research is if the scar in the fingerprint image could be removed, then the accuracy of minutiae extraction can be increased. This research aims to develop an image enhancement approach to improve the quality of the scarred fingerprint images to generate an accurate minutiae extraction result. The objectives to be achieved from this research are: 1. To develop a method for removing noise in the fingerprint images and at the same time to enhance the level of contrast. 2. To improve the current ridge structure enhancement algorithm to reconstruct the broken ridges affected by scars. 3. To evaluate the effectiveness of the proposed enhancement approach by using the extracted minutiae. In order to reach the objectives, there are four main stages involved: preprocessing; image enhancement; feature extraction; and evaluation. Preprocessing occupied an image cropping process to remove the unwanted area in the fingerprint images. In the image enhancement stage, there are two main processes that need to be done are noise removal and ridges structure enhancement. The image enhancement process is essential to improve the quality of fingerprint images. Then, minutiae will be extracted in the feature extraction stage by using the minutiae marking method. Finally, the proposed image enhancement approach’s performance and effectiveness will be measured in the evaluation stage. For this purpose, only scarred fingerprint images will be used. So, the contributions of this research can be summarized into three achievements, which are noise removal technique, ridges structure 123 enhancement method, and the improved results of the quality index. The organization of this paper is as follows: In Sect. 2, a review of previous studies related to scar finger images is inve (...truncated)