A Method of Colour-Histogram Matching for Nigerian Paper Currency Notes Classification

Simple item page
dc.contributor.authorOmeiza, I. O. A., Ogunbiyi, O., Ogundepo, O. Y., Otuoze, A. O., Egbune, D. O., & Osunsanya, K.
dc.date.accessioned2024-09-15T15:47:11Z
dc.date.available2024-09-15T15:47:11Z
dc.date.issued2023
dc.description.abstractIn this paper a new algorithm for the classification of three Nigerian paper currency notes, namely 200, 500, and 1000 Naira (N) denominations is presented. The work examines the effectiveness of using only colour histograms to differentiate between the classes or denominations of the three Nigerian paper currency notes. The bin-heights of the histograms of the HSI component images for the paper currencies are used as features while a rule-based classifier designed to take advantage of the changes or variations in the histogram patterns is used to classify the paper currencies into the right denomination class. The algorithm involves the utilization of a simple and effective comparison strategy as opposed to the existing, too-rigid metrics for histogram-comparison used by other authors for color indexing in content-based image retrieval systems. Over a testing data-set of 300 samples, the algorithm achieved an average classification accuracy of 98.66%, and classification accuracies of 100%, 99% and 97% for the N=200, N=500 and N=1000 denominations, respectively. The proposed algorithm does not require extensive preprocessing of the paper-currency images and as such is fast in implementation.
dc.identifier.urihttps://kwasuspace.kwasu.edu.ng/handle/123456789/2375
dc.language.isoen
dc.publisherJordan Journal of Electrical Engineering (JJEE)
dc.titleA Method of Colour-Histogram Matching for Nigerian Paper Currency Notes Classification
dc.typeArticle
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
A Method of Colour-Histogram Matching for Nigerian Paper.pdf
Size:
1.12 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed to upon submission
Description:
Download
Collections
Scholarly Publication