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We present a method to learn and recognize object class
models from unlabeled and unsegmented cluttered scenes
in a scale invariant manner. Objects are modeled as flexible
constellations of parts. A probabilistic representation is
used for al
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算法通过将二维直方图分为四部分：背哥、目标．受噪声干扰的背景和受噪声干扰的目标，以选取这四部分的信息熵的和最大作为闽值的选取准则。访方法有三个优点：尽可能包括背罱部分和目标部分；可以有效地提高对噪声敷据的鲁棒性；不过度地引入噪声和边缘信息。实验结果表明，谊方法具有较好的图像分割效果。-Through two-dimensional histogram algorithm will be divided into four parts: back elder brother, target. By
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threshold is a key technique for the segmentation and edge detection in an image for image processing. Here in this file the threshold is on the based of the maximum entropy of an image using shannon entropy method.
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Probe into Image Segmentation Based on Sobel Operator and Maximum Entropy
Algorithm
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利用最大熵法在MATLAB软件上对图像进行阈值分割，程序亲测可行(Maximum entropy method for image segmentation)
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