4/15/2023 0 Comments Flowchart skripsi program loginproposed a self-supervised algorithm to classify all the image patches in an image into water or not-water category by features of RGB, texture, and height. For Machine Learning-based methods, Achar et al. The texture and structure of images are also widely used in related research in water scenes such as waterline detection and maritime horizon line detection. used the adaptive threshold Canny edge detection algorithm to detect the river boundary. Then a designed texture feature is used to perform K-Means clustering on each 9 × 9 small patch in the image, where the class with the smallest average value of texture is classified as the water region, where the detection of water region with shadow needs the aid of stereo vision. Yao used the Region Growing method firstly to separate the obvious water region based on the brightness value. combined the color and texture features to detect the water region according to the appearance characteristics of the river in the outdoor scene. For image processing-based methods, Rankin et al. For water region segmentation, researchers have explored different kinds of methods that fall into three main categories-image processing-based methods, Machine Learning-based methods (including Deep Learning, Supervised Learning, Clustering, etc.), and hardware-based methods.
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