Abstract

Image edge information is essentially one of the most significant information in an image, which can describe the target outline, its relative position within the target area, and other important information. Edge detection is one of the most important process in image processing, and the detection results directly affects the image analysis. Traditional edge detection algorithms are accomplished through detecting the maximum value of the first derivative or zero crossing of the second derivative. Though it seems the representative first order differential operators have known advantages like simple computation, speed and ease of implementation, they are more sensitive to noise and their detection effect are not perfect in most engineering application. Schemes for counterfeit detection has been continuously evolving through various techniques and algorithms run on machines and devices. This paper presents image enhancement and image sensing through the use of Canny Edge Technology. Moreover, counterfeit detection on selected Philippine banknotes was achieved by incorporating a distinct security feature known as Optically Variable Device (OVD) patch, as an improvement to the traditional three-way detection of bills (watermark, security thread, see-through marks)A MATLAB GUI program was developed that acquired and processed the image through Canny Edge Technology. The Canny Edge algorithm proved a robust method in detecting fake bills through OVD security features, revealing statistically significant detection proportion under a 5% level of significant for the four cases under test.

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