Abstract
Almond is a product with high nutritional and economic value; some quality control procedures are applied before the almonds are packaged. Applications such as product classification, faulty product detection, and non-product substance detection are widely used in quality control processes. With the development of image processing and camera control systems, these operations can be performed with computer vision systems at low costs, high speed and accuracy. In this study, to detect broken almonds; image processing techniques such as thresholding, HSV transformation and blob detection were actively used. Binary image followed by blob detection algorithm was used to detect almonds. HSV transformation was performed on the detected almonds to detect the broken area. It is aimed to detect broken areas by applying appropriate threshold values to H and S bands. When the proposed method was tested, an algorithm was developed that worked 100% as long as the broken areas were visible.
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