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Morphological Thinning in OpenCV
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Morphological thinning, also known as skeletonization, is a computer vision technique ud to extract the shape of an object. In OpenCV, morphological thinning is performed using the "cv::morphologyEx" function with the "MORPH_THINNING" flag.
jigsawMorphological thinning works by iteratively removing pixels from the edges of an object until it is reduced to a single-pixel thickness. This process prerves the overall shape and topology of the object while removing unnecessary details.
colors of the windTo perform morphological thinning in OpenCV, the input image must first be converted to a binary image. This can be done using the "cv::threshold" function with a suitable threshold value.救护车英语
Once the binary image is obtained, morphological thinning can be achieved using the "cv::morphologyEx" function with the "MORPH_THINNING" flag. The function takes two par
ameters: the input image and a structuring element.绝望的主妇第7季
foundation是什么意思The structuring element is a small binary image that defines the shape and size of the pixels to be removed during thinning. Common structuring elements include the "cv::getStructuringElement" function, which can generate rectangular, elliptical, and cross-shaped elements.docking
After applying the morphological thinning operation, the resulting image will contain the skeleton of the input object. This can be ud for various purpos, such as shape analysis, object recognition, and image processing.
say hello什么意思In summary, morphological thinning is a powerful tool in computer vision that can be ud to extract the shape of an object. OpenCV provides a convenient function for performing thinning, which involves converting the input image to binary, defining a structuring element, and applying the "cv::morphologyEx" function with the "MORPH_THINNING" flag.
