CHALLENGES IN INDIAN CURRENCY DENOMINATION RECOGNITION &amp; AUTHENTICATION

Ali, Syed Ejaz; Mukherjee, Subra

doi:10.15623/ijret.2014.0311082

Cited by 3 publications

(2 citation statements)

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“…In the domain of currency recognition, authentication and detection some work during the mid teens had also been started by various researchers. In the year 2014 (Ali, Gogoi & Mukherjee, 2014) presented a paper that intended to represent an extensive survey of recent technological trends in the recognition and authentication of paper currency notes while identifying the various challenges. They had mentioned the significance of various security features of an Indian banknote along with the classification of various detection techniques of the security features based on first and second line inspection methods.…”

Section: Literature Reviewmentioning

confidence: 99%

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2023

J. Graph. Eng. Des.

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In this paper the different salient features of the old and new version of Indian paper currency notes have been studied and compared. The list of security features of Indian currencies have been mentioned and discussed. Various kinds of conventional methods that are used to detect authenticity and to recognize a note has been explained. It has been observed that each technique has its own objective and significance. There are many conventional tools that can be used to recognize different features of a note. To classify different techniques, the detection method comprises of two parts i.e., the first line detection method and the second line detection method. Physical dimensions of a paper note along with its thickness have pointed out a new parameter which is the diagonal of a genuine currency note that has been calculated to obtain a proposed standardization and each value differs from different denominations. The classification of different Indian banknotes giving emphasis on its characteristics, both salient and security features, dimensions and detection methods has been mentioned and briefly explained. For validation of the paper currencies two methods have been discussed emphasizing on fuzzy logic framework by taking into consideration a 3-point likert scale and another validation methodology using digital image processing.

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Section: Literature Reviewmentioning

confidence: 99%

“…A second-line inspection method doesn't include verification of currency notes by the naked eye alone, and thus requires a device to perform the authentication function. These devices are more secure and can quickly detect the counterfeit notes than the visual methods (Ali, Gogoi & Mukherjee, 2014).…”

Section: Detection Techniques Of Currency Notesmentioning

confidence: 99%

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2023

J. Graph. Eng. Des.

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Geometric and Grayscale Template Matching for Saudi Arabian Riyal Paper Currency Recognition

Aulia

Budhi

Rusdinar

et al. 2018

IJECE

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<p>Detecting the authenticity of paper currencies using automated based Paper Currency Recognition (PCR) with image processing techniques was still a hot topic of discussion, due to the circulation of counterfeit currency that was still overwhelming in some countries. There was a downside along with this advancement in technology in the field of color printing, duplication, and scanning, because it was became one of the supporting factors of the increasing crime rate in production of counterfeit money. Our system has performed a PCR approach based on image processing techniques. In this study, the SAR banknote was the object to be recognized and detected its authenticity with the development of the previous method, which was incorporating the Geometric Template Matching and Grayscale Template Matching. In addition to the pattern recognition process, the classification process on 1 SAR, 2 SAR, 5 SAR, and 10 SAR was also performed. From PCR test up to 100 sample data, for each tested banknote value obtained the average value of the best accuracy level from incorporating GeoMatchingScore and GrayMatchingScore for the classification process was 95.25%. While the average level of system accuracy in recognizing counterfeit money on each banknote obtained a maximum value of 100%.</p>

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Detection Method for Counterfeit Currency Based on Bit-Plane Slicing Technique

Alshayeji¹,

Al-Rousan²

2015

IJMUE

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Counterfeiting and forging currencies is a serious threat to any economy. Even though currency exists as a variation of coins, banknotes, and electronic data, many economies remain threatened by counterfeiting which is made possible by the ongoing technological advancements in reprographic equipment available to the general public. Clearly, counterfeit currency detection is not a task that can be neglected. Digital image processing is one of the most common and effective techniques used to distinguish counterfeit banknotes from genuine ones. A new approach is presented in this paper using the bit-plane slicing technique to extract the most significant data from counterfeit banknote images with the application of an edge detector algorithm. The proposed technique consists of decomposing original images of 256 gray levels into their equivalent 8 binary images. This is useful in analyzing the relative importance contributed by each bit of the original image. Higher order bit levels are evaluated for grayscale banknote images with the application of Canny edge detection algorithm. The results are then compared with genuine banknotes and with other existing techniques used for detecting counterfeit notes. Unlike existing research, it was observed that the edges obtained using bit-plane sliced images are more accurate and can be detected faster than obtaining them from the original image without being sliced. The detection of counterfeit currency was also achieved by following the process of using Canny edge detection, image segmentation, and feature extraction. 226Copyright ⓒ 2015 SERSC brightness [3]. These dots are picture elements and are referred to as pixels. A grayscale image is the preferred format for image processing in this paper. When the acquired images are of Red-Green-Blue (RGB) color, they can be decomposed and processed as three separate grayscale images for simplicity.When processing digital images, the images have to go through several phases before beneficial information can be extracted from the image. Images of scanned currency notes used in this paper will undergo the following phases: image acquisition, pre-processing an image, bit-plane slicing, edge detection, image segmentation, and feature extraction. Enhancing images may not always be the answer for image analysis, depending on the application. This can be resolved using bit-plane slicing where relative information can be extracted from each bit-plane [4].In this paper, Section 2 discusses existing work related to currency recognition and the detection of counterfeit currency. Section 3 and 4 briefly explain counterfeit currency and digital image processing, while Section 5 describes the proposed method using bit-plane slicing technique. Section 6 explains the evaluation measures to be considered and presents a case study on the Kuwaiti currency notes. Section 7 discusses experiments performed and the results achieved, with an analysis and a discussion of the results, and Section 8 draws conclusions from experimental results and possible fu...

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CHALLENGES IN INDIAN CURRENCY DENOMINATION RECOGNITION & AUTHENTICATION

Cited by 3 publications

References 10 publications

Untitled

Untitled

Geometric and Grayscale Template Matching for Saudi Arabian Riyal Paper Currency Recognition

Detection Method for Counterfeit Currency Based on Bit-Plane Slicing Technique

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