Digital Surface Area Measurement as a Tool for Advanced Leather Quality Assurance

Abstract

In this paper, a novel approach is presented for accurately detecting the surface area of an irregular leather piece using image processing techniques. The method involves a sequence of steps beginning with the extraction of frames from a running video of the leather piece, which are subsequently converted into grayscale images for further processing. A smoothing algorithm is applied to reduce noise and improve the quality of the images, followed by thresholding to differentiate between the leather material and the background. Subsequent contour detection isolates the leather piece by converting the background to black pixels, while the leather itself is turned into white pixels. The area of the leather is then computed by counting the number of white pixels, which represent the leather material. To obtain the leather's actual surface area, we introduce a conversion unit that multiplies the white pixel count, providing a direct measurement of the leather's surface area. This method offers a valuable tool for leather industries, where precision in measuring irregular shapes is critical, and can potentially replace traditional manual measurements with an automated, more accurate system.