Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Mopuru, Bhargavi; Sinha, Anurag; Agrawal, Ankita; Nandan, Amritesh; Agarwal, Ankit; Nikitha, Peddi; Sharma, Vandana; Anand, Ankit; Keskin, Do?an; Kumar, Biresh; Jha, Pooja Title A name given to the resource Improved Indian currency recognition: neighbourhood-centred image processing and CNNs with region of pixel selection techniques Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived International Journal of Services, Economics and Management;Volume;16;Issue;2026-05-04 00:00:00;pp.482-516 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1504/IJSEM.2025.148476" target="_blank" rel="noreferrer noopener">https://doi.org/10.1504/IJSEM.2025.148476</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105015973816?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105015973816?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mopuru B., Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Andhra Pradesh, 520002, India; Sinha A., Department of Computer Science, IGNOU, India; Agrawal A., Department of Commerce, Indian Institute of Management Kozhikode Kerala, Kozhikode, India; Nandan A., Department of Computer Science, Graphic Era (Deemed to be University), Uttarakhand, 248002, India; Agarwal A., Department of Computer Science and Engineering, Kalasalingam Academy of Research and Education, Krishnankoil, Tamil Nadu, Virudhunagar, India; Nikitha P., Department of Computer Science and Engineering, Kalasalingam Academy of Research and Education, Krishnankoil, Tamil Nadu, Virudhunagar, India; Sharma V., Department of Computer Science, CHRIST (Deemed to be University), Delhi NCR, India; Anand A., Department of Computer Science, Amity University, Jharkhand, India; Keskin D., Department of Computer Science, Turkish German University, Istanbul, Turkey; Kumar B., Department of Information Technology, Amity University Jharkhand, Ranchi, India; Jha P., Department of Information Technology, Amity University Jharkhand, Ranchi, India Description An account of the resource The paper proposes an improved approach for Indian currency recognition using neighbourhood-centred image processing and convolutional neural networks (CNNs) with region of pixel selection techniques. The method includes image pre-processing steps such as noise reduction, contrast enhancement, and resizing. A neighbourhood-centred image processing technique is applied to capture contextual information from local neighbourhoods around each pixel. A CNN-based model is then trained on the pre-processed images to learn discriminative features for currency recognition. To enhance accuracy and efficiency, a region of pixel selection technique is introduced to select only relevant regions of interest for CNN training and inference, reducing computational overhead. Experimental results demonstrate the effectiveness of the proposed approach, achieving high accuracy in currency recognition and improved efficiency in terms of computational time and memory requirements. The proposed method has potential applications in automated cash-handling machines, vending machines, and mobile payment systems where reliable currency recognition is essential. Copyright 2025 Inderscience Enterprises Ltd. Subject The topic of the resource CNN; currency recognition; decision boundary; features; image processing; image processing; RGB; threshold Publisher An entity responsible for making the resource available Inderscience Publishers Relation A related resource ISSN: 17530822; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online