Colour Space Selection for Entropy-based Image Segmentation of Folded Substrate Images

This paper is focused on analysing the effects of the chosen colour space on image segmentation accuracy for a permanent quality control of the folding process. The folding process is one of the basic operations in print finishing, but during this converting operation the printed or non-printed substrates are exposed to high tensile stresses. These stresses can cause coating cracks on the folding line, which decrease the expected aesthetic feature or even the functionality of the product. High production efficiency of the folding process could be provided by a control system for automated visual inspection. Such a quality control algorithm was proposed by the authors in previous papers. Since the proposed algorithm relies on qualitative image segmentation, it is very important to determine all the factors which influence the segmentation quality. This paper investigates the influence of colour spaces. The applied image segmentation algorithm (Maximum Entropy) works on grey-scale images, and therefore only the luminance components of the five selected colour spaces (HSI, HSL, HSV, CIE Lab and CIE xyY) were used. The segmentation quality was determined by using six different measures (quantitative and qualitative), which were combined in order to obtain a single performance measure for algorithm evaluation.