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PCB Image Enhancement Algorithm Based on Double Sigmoid Transform |
GUO Fenglin, GUAN Shu'an |
Department of Computer and Information Engineering, Wuhan Polytechnic University, Wuhan 430023, China |
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Abstract: In the Printed Circuit Board (PCB) defect detection based on Automatic Optic Inspection (AOI), the actually collected PCB images are often blurred over the edge, especially in the area of dense vertical lines. Therefore, to eliminate noise and enhance the image to highlight the edge, which makes the alignment between PCB sample and the detected PCB easer and more precise and avoid missing and false detection, are needed. The main target for enhancing PCB images is to sharp the edges, at the same time to effectively suppress noise, especially the noise near the edges. From the perspective of the edge sharpening, the differential operation should be used. However, for filtering out the noise, integral operation should be applied to. Based on the above features, a new image transformation i.e. double Sigmoid transformation, which imposes a double transformation on the original image and at the same time uses the results with the transformation to enhance the original image, is presented. At first, a definition of Sigmoid transformation is given, and then double Sigmoid operators are deduced. In order to simplify the computing, only a set of special feature value is taken to calculate the sigmoid operator, which makes the computing speed faster. Experiments show that the Sigmoid algorithm could effectively sharpen PCB image edges, at same time, filter out noise in the image. Even if the original PCB image is not distinct enough and uniform brightness, the algorithm is still able to precisely locate circuit edge, which could make the edge extracting and edge recognition easier.
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Received: 21 February 2011
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