Using the grey level histogram to distinguish between roughness of surfaces

AbstractIn recent years, the advent of high-speed general-purpose digital computers and vision systems has made image analysis easier and more flexible. Images of surfaces captured using vision systems can be used to identify surface texture. In this paper, a new method, called the best grey level histogram (BGLH), is introduced to get the most accurate image of a surface for the purpose of surface texture assessment. A program was written using MS Visual C++ to calculate and display the grey level histogram for any grey image. The software is capable of converting the colour images to grey images. The program is capable of reading six different image file formats; these are BMP, TIFF, GIF, PCX, JPG and WMF. The conversion method depends on calculating three items from the grey levels of the image. These items are the minimum non-zero grey level, the maximum non-zero grey level and the number of used grey levels for the captured image. Many factors affect the quality of the captured image such as the brig...