Abstract
Image processing techniques are highly recommended for industrial purposes. Its advantages include fast processing speed, high-quality inspection, and great efficiency. Also, the process can be repeated as many times as required without affecting the efficiency. The aim of this project is the detection of corrosion on PCB by the use of k-means clustering for colour-based segmentation and image processing theories. This project requires a test image and no-reference image. The algorithm can be applied directly to the coloured image. The corrosion is detected on the basis of the colour information by applying a clustering algorithm, viz. k-means. This is an iterative clustering technique. As compared to other hierarchical clustering techniques, k-means is the simplest. Its implementation is easy and massive data is reorganized into more formal groups. Moreover, this method produces tighter clusters than other hierarchical clustering. It is computationally faster provided that the number of clusters chosen is small.
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