| 基于局部密度和偏移量的图像自动分割算法 |
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| 引用本文：刘娜?覮，刘向阳.基于局部密度和偏移量的图像自动分割算法[J].计算技术与自动化,2020,(1):128-132 |
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| 中文摘要:图像分割是计算机视觉领域的传统问题，也是图像分析和模式识别的关键组成部分。提出了一种不依赖于图像分割数参数的图像自动分割算法。基于超像素间的测地距离，根据其定义的局部密度和偏移量，结合K-S假设检验来分析图像最佳分割数，并给出了图像自动分割算法。大量图像分割的实验结果表明：该方法可以准确地对图像进行自动分割，达到了较好的分割效果，相比其它方法，速度更快。 |
| 中文关键词:测地距离 图像分割数 图像自动分割 局部密度 偏移量 |
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| Automatic Image Segmentation Algorithm Based on Local Density and Offset Distance |
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| Abstract:Image segmentation is a traditional problem in the field of computer vision and a key component of image analysis and pattern recognition. This paper proposes an automatic image segmentation algorithm that does not depend on the number of image segmentation parameters. Based on the geodesic distance between superpixels，according to its defined local density and offset distance，we combine the K-S hypothesis test to analyze the optimal segmentation number of the image and automatically segment the image. The experimental results of a large number of image segmentation show that the method can accurately segment the image automatically and achieve better segmentation effect. Compared with other methods，the speed is faster. |
| keywords:geodesic distance image segmentation number automatic image segmentation local density offset distance |
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