In Digital image processing, the given image is broken down into many pixels and a numerical value is attributed to each of the pixel resulting in an array of numbers. These numbers are analyzed to get the required information from the image. It is used in Optical character recognition, Medical imaging analysis, Digital photoelasticity, Digital image correlation and real time sports analysis.
Pre-processing an image refers to applying filters to the image to get a better image in terms of contrast, brightness and similar parameters. Also, color adaptation techniques require pre-processing an image where there is a background color.
Thresholding an image is the process in which the grey-scale image is converted to a binary image based on a specific threshold value. All the pixels having the grey-scale value above the threshold value are converted to white pixels and the ones below to black. Important criteria to determine the threshold value are the fringe contour and fringe thickness. For a high value, we get a very dark image, hence we should optimize the value
Semi-thresholding is the process in which all pixels below the threshold value are changed to black whereas the ones above are left untouched.
Fringe thinning and fringe ordering will give us the result using a single image whereas phase shifting interferometry requires different positions.
Fringe thinning is of two types, binary based and intensity based. Chen and Taylor algorithms are used to obtain fringe thinning. Also, we can use logical operators to to do the fringe thinning.
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