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 Conference Paper Faculty Publications- Conference Papers 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 Sharmila, B.; Sowmiya, A.; Mary, Teena; Sandeep, J.; Sreeja, C.S. Title A name given to the resource A Comprehensive Survey of Methods for Identifying Counterfeit Banknotes Using Image Processing and Machine Learning 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 Lecture Notes in Networks and Systems;Volume;1164 LNNS;pp.555-573 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-97-8329-8_41" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-97-8329-8_41</a> <br /><br /><a href="https://www.scopus.com/pages/publications/85219207663?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/85219207663?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 Sharmila B., CHRIST University, Dharmaram College Post, Hosur Road, Karnataka, Bengaluru, 560029, India; Sowmiya A., CHRIST University, Dharmaram College Post, Hosur Road, Karnataka, Bengaluru, 560029, India; Mary T., CHRIST University, Dharmaram College Post, Hosur Road, Karnataka, Bengaluru, 560029, India; Sandeep J., CHRIST University, Dharmaram College Post, Hosur Road, Karnataka, Bengaluru, 560029, India; Sreeja C.S., CHRIST University, Dharmaram College Post, Hosur Road, Karnataka, Bengaluru, 560029, India Description An account of the resource The world economy is threatened by counterfeit currencies. Counterfeit currencies are often difficult, time-consuming and ineffective to identify manually. Automated methods based on image processing techniques and machine learning algorithms are helpful in detecting counterfeit notes. This survey paper reviews the current strategies on fake banknote detection using image processing techniques and machine learning algorithms. We discuss various stages of the detection process, including image acquisition, preprocessing, feature extraction and classification. Furthermore, we analyze the limitations and comparative performance of different algorithms and approaches mentioned in the literature. The survey aims to provide insights into the various methodologies, challenges and future directions in the field of fake banknote detection, facilitating the development of more robust and effective counterfeit detection systems. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. Subject The topic of the resource CNN; Counterfeit banknotes; Fake currency detection; Image processing; KNN; Machine learning; Security features; SVM Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-981978328-1; Language A language of the resource English Type The nature or genre of the resource Conference paper 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