Klasifikasi Telur Ayam menggunakan Deteksi Tepi Operator Canny


  • Laila Arfiah Erda Politeknik Caltex Riau


Middle to lower class farms usually classify chicken eggs by visual viewing and feeling the weight of the eggs according to estimates. As the results of the classification of chicken eggs are not accurate. The final project entitled "Classification of Chicken Eggs using Canny Operator Edge Detection" is expected to provide more accurate results than manual classification. The operator can smooth the image using a gaussian filter to remove noise. Furthermore, searching the edges in determining the gradient of the image will mark the area of high derivative spatial value with the entire area and its background. The resulting outline is then thinned out so that the shape of the object is more clearly visible. In this final project, an image of a chicken egg was photographed using a 12mp HP camera on a flat surface with a distance of 20cm. Image using laptop into matlab software R2013a using canny operator edge detection and applied via GUI (Graphical User Interface). After the experiment was carried out on 7 chicken eggs, an accuracy of 100% match between the measured results was obtained using operator edge detection and manual calculations. Keywords: Edge Detection, Canny Operator, Matlab, GUI, Egg Classification.