Oftentimes I see computer vision researchers and developers trying to solve a problem and immediately dive into advanced computer vision, machine learning, and deep learning techniques. Morphological operations are one of my favorite topics to cover in image processing.īecause these transformations are so powerful. Why learn about morphological operations?įigure 1: Morphological operations are a set of basic image processing techniques that you need to understand to be a successful computer vision practitioner. If this sounds confusing, don’t worry - we’ll be reviewing many examples of each of these morphological transformations, and by the time you are done reading through this tutorial, you’ll have a crystal clear view of morphological operations. There are many different morphological transformations that perform “opposite” operations from one another - just as addition is the “opposite” of subtraction, we can think of the erosion morphological operation as the “opposite” of dilation. This explanation of a structuring element may sound vague - that’s because it is. And based on the given operation and the size of the structuring element we are able to adjust our output image. This structuring element defines the neighborhood to be examined around each pixel. Morphological operations “probe” an image with a structuring element. We can also utilize morphological operations to close gaps between objects as well as open them. We can use morphological operations to increase the size of objects in images as well as decrease them. More specifically, we apply morphological operations to shapes and structures inside of images. Morphological operations are simple transformations applied to binary or grayscale images. Looking for the source code to this post? Jump Right To The Downloads Section OpenCV Morphological Operations
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