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OTSU1Dmy
- 灰度图像二值化分割，一维大津法或称为一维最大类间方差法-1D Maximum Between-Cluster
OTSU2Dmy
- 灰度图像分割，二维大津法或二维最大类间方差法-2D Maximum Between Cluster Variance
OTSU3Dmy
- 灰度图像分割，三维大津法或三维最大类间方差法-3D Maximum Between Cluster Variance
otsu
- otsu算法确定二值化阀值，最大类间方差是由日本学者大津(OTSU)于1979年提出的,是一种自适应的阈值确定的方法,又叫大津法,简称OTSU。 -In computer vision and image processing, Otsu s method is used to automatically perform histogram shape-based image thresholding,[1] or, the reduction of a graylevel image t
OTSU1
- 。图像分割算法中最大类间方差法(OTSU)实现图像二值化,可以将图像分为目标类和背景类，便于后续处理。-. Image segmentation algorithm Otsu method (OTSU) for image binarization, image can be divided into the target class and background class, easy to subsequent processing.
基于最大类间方差阈值与遗传算法的道路分割
- 最大类间方差法是由日本学者大津(Nobuyuki Otsu)于1979年提出的,是一种自适应的阈值确定的方法,又叫大津法,简称OTSU。它是按图像的灰度特性,将图像分成背景和目标2部分。背景和目标之间的类间方差越大,说明构成图像的2部分的差别越大,当部分目标错分为背景或部分背景错分为目标都会导致2部分差别变小。(The largest between-class variance method was proposed by the Japanese scholar Nobuyuki Otsu