Philippine currency paper bill counterfeit detection through image processing using Canny Edge Technology

Ballado, Alejandro H.; Cruz, Jennifer C. Dela; Avendano, Glenn O.; Echano, N. M.; Ella, J. E.; Medina, Mt; Paquiz, B.K.C.

doi:10.1109/hnicem.2015.7393184

Cited by 23 publications

(5 citation statements)

References 5 publications

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“…Then, the total effectiveness average is 96.5%, which are results that could improve with a bigger sample. Compared to other studies with different currencies, it reached a higher percentage than Ballado's (95%) [6] and a lower percentage than Han's (100%) [7].…”

Section: Resultscontrasting

confidence: 78%

“…In comparison, our proposed solution does use an enclosure to ensure uniform illumination across all processed training and validation images. Publications such as [5] and [6] that are based on digital image processing techniques have some flaws, as they did not consider the use of supervised learning algorithms to solve the classification task. On the contrary, our proposed solution uses a support vector machine (SVM) to tackle the classification problem after a training process performed with labeled images.…”

Section: Literature Reviewmentioning

confidence: 99%

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An algorithm for Peruvian counterfeit Banknote Detection based on Digital Image Processing and SVM

Huaytalla¹,

Humari²,

Kemper³

2021

Adv. sci. technol. eng. syst. j.

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In this work we propose an algorithm for Peruvian counterfeit banknotes detection. Our algorithm operates in banknotes with 50, 100 and 200 soles denominations that were manufactured from 2009 onwards. This algorithm offers an automatic diagnosis based on digital image processing and support vector machines (SVM). Current Peruvian counterfeit detection systems are specially designed to analyze relevant characteristics in dollars and euros. Then, some counterfeiters can fool these systems. We made our detection system robust because we focus on the image acquisition and the segmentation of intaglio marks engraved over the banknotes. After segmentation, we applied embossing and Sobel filters followed by an aperture morphological operation to obtain special characteristics that were then classified by an SVM. We have validated our methodology using real and fake banknotes from a dataset of 240 samples provided by Central Reserve Bank of Peru (BCRP). Our final identification accuracy was 96.5%.

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Section: Resultscontrasting

confidence: 78%

Section: Literature Reviewmentioning

confidence: 99%

An algorithm for Peruvian counterfeit Banknote Detection based on Digital Image Processing and SVM

Huaytalla¹,

Humari²,

Kemper³

2021

Adv. sci. technol. eng. syst. j.

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“…From the previous years, there were numerous machine vision systems proposed by local and foreign authors due to their many advantages. These include the work of [14][15][16][17]. The promising results from these studies benefitted the progress and the development of this study.…”

Section: Various Machine Vision Systemmentioning

confidence: 99%

An Automated Candling System for Duck Egg Fertility Detection, Sorting, and Counting via Digital Image Processing

2021

Proceedings of 2021 the 11th International Workshop on Computer Science and Engineering

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Duck farming is considered one of the lucrative livelihoods in the Philippines because of its many advantages with minimal cost and high-profit returns. This is the second-largest poultry industry in the country, yet this industry is still immature and underdeveloped. There were many attempts done to improve the egg production sector of the poultry industry, particularly in the candling method. However, they mainly focused on chicken eggs. Hence, automating the candling system for the incubated duck eggs would be beneficial. The main objective of this study was to create an automated candling system for duck egg fertility detection, sorting, and counting via digital image processing. The hardware of the proposed system was made from locally available components, materials, and equipment. The most suitable light source was assessed, and it was found out that a 9W White LED would give the optimum results among the tested light bulbs. The camera was also calibrated and was placed three inches away from the incubated duck egg and was mounted ninety degrees from the horizontal. The fastest allocated processing time that would give a high fertility detection accuracy was assessed and was determined to be 2.5 seconds. The classification model was created in TensorFlow and was evaluated using a confusion matrix. The results showed that the classification accuracy was 0.86, f-measure was 0.875 and MCC was 0.7417. The functionality was also assessed and was 100% functional. The accuracy of the machine to detect the fertility of 5-, 6-, 7-, 8-, 9-and 10-day old, incubated duck eggs were also tested and were found out to be 50%, 60%, 90%, 100%, 80%, and 80% accurate, respectively. The counting of total inputted duck eggs and total sorted "balut" and "penoy" was also 100% accurate. Lastly, the efficiency of the system was evaluated by calculating the overall equipment effectiveness and was found out to be 83.99% efficient.

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“…Image processing is commonly used for detection purpose. 1) Counterfeit Detection of Paper Bill: [2] uses Canny Edge Technology which presents image enhancement and image sensing.…”

Section: Related Workmentioning

confidence: 99%

Fake Product Identifier

Rathod¹

2019

IJRASET

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Counterfeit consumer goods are goods, often of inferior quality, made or sold under another's brand name without the brand owner's consent. Sale of these goods still remains a significant problem for shoppers. Grammatical and spelling mistakes, flawed fonts and logos, missing accessories, minute changes in design are some of the ways these products can be recognized as counterfeit. Our project aims at identifying such goods through photos captured by the user of the product. Product counterfeiting is a serious problem causing the industry estimated losses of billions of dollars every year. With the increasing spread of e-commerce, the number of counterfeit products sold online increased substantially. We propose the adoption of a semi-automatic workflow to identify likely counterfeit offers in offline platforms. The workflow includes steps to generate search queries for relevant product offers, to match and cluster similar product offers, and to assess the counterfeit suspiciousness based on different criteria. The goal is to support the periodic identification of many counterfeit offers with a limited amount of manual effort.

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Philippine currency paper bill counterfeit detection through image processing using Canny Edge Technology

Cited by 23 publications

References 5 publications

An algorithm for Peruvian counterfeit Banknote Detection based on Digital Image Processing and SVM

An algorithm for Peruvian counterfeit Banknote Detection based on Digital Image Processing and SVM

An Automated Candling System for Duck Egg Fertility Detection, Sorting, and Counting via Digital Image Processing

Fake Product Identifier

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