Invariant image-based currency denomination recognition using local entropy and range filters

Anwar H, Ullah F, Iqbal A, Ul Hasnain A, Ur Rehman A, Bell P, Kwak D (2019)

Publication Type: Journal article

Publication year: 2019

Journal

Entropy MDPI

Book Volume: 21

Article Number: 1085

Journal Issue: 11

DOI: 10.3390/e21111085

Abstract

We perform image-based denomination recognition of the Pakistani currency notes. There are a total of seven different denominations in the current series of Pakistani notes. Apart from color and texture, these notes differ from one another mainly due to their aspect ratios. Our aim is to exploit this single feature to attain an image-based recognition that is invariant to the most common image variations found in currency notes images. Among others, the most notable image variations are caused by the difference in positions and in-plane orientations of the currency notes in images. While most of the proposed methods for currency denomination recognition only focus on attaining higher recognition rates, our aim is more complex, i.e., attaining a high recognition rate in the presence of image variations. Since, the aspect ratio of a currency note is invariant to such differences, an image-based recognition of currency notes based on aspect ratio is more likely to be translation- and rotation-invariant. Therefore, we adapt a two step procedure that first extracts a currency note from the homogeneous image background via local entropy and range filters. Then, the aspect ratio of the extracted currency note is calculated to determine its denomination. To validate our proposed method, we gathered a new dataset with the largest and most diverse collection of Pakistani currency notes, where each image contains either a single or multiple notes at arbitrary positions and orientations. We attain an overall average recognition rate of 99% which is very encouraging for our method, which relies on a single feature and is suited for real-time applications. Consequently, the method may be extended to other international and historical currencies, which makes it suitable for business and digital humanities applications.

Authors with CRIS profile

Hafeez Anwar Juniorprofessur für Digital Humanities mit Schwerpunkt Kunstgeschichte Peter Bell Juniorprofessur für Digital Humanities mit Schwerpunkt Kunstgeschichte

Additional Organisation(s)

Department Informatik, AG Digital Humanities Interdisziplinäres Zentrum für Digitale Geistes- und Sozialwissenschaften

Involved external institutions

COMSATS University Islamabad (CUI) / / COMSATS Institute of Information Technology (CIIT) PK Pakistan (PK) Kean University US United States (USA) (US) Inha University / 인하대학교(仁荷大學校 KR Korea, Republic of (KR)

How to cite

APA:

Anwar, H., Ullah, F., Iqbal, A., Ul Hasnain, A., Ur Rehman, A., Bell, P., & Kwak, D. (2019). Invariant image-based currency denomination recognition using local entropy and range filters. Entropy, 21(11). https://dx.doi.org/10.3390/e21111085

MLA:

Anwar, Hafeez, et al. "Invariant image-based currency denomination recognition using local entropy and range filters." Entropy 21.11 (2019).

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