排序方式: 共有399条查询结果,搜索用时 16 毫秒
101.
徐寒 《数字社区&智能家居》2006,(14)
掌纹图像的分割是针对一幅掌纹,找出感兴趣的目标区域(ROI),使之从背景中分离出来,它是掌纹特征提取和进一步的匹配的关键步骤。传统的Otsu阈值化算法能有效地将掌纹从背景中分离,通过旋转与平移,使掌纹图像进一步精确定位与归一化,并选择纹线集中的部分实现了在线掌纹图像的分割。实验结果验证了此法的有效性。 相似文献
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Mohamed Abdel-Basset Reda Mohamed Mohamed Abouhawwash Ripon K. Chakrabortty Michael J. Ryan Yunyoung Nam 《计算机、材料和连续体(英文)》2021,68(3):2961-2977
Image segmentation is vital when analyzing medical images, especially magnetic resonance (MR) images of the brain. Recently, several image segmentation techniques based on multilevel thresholding have been proposed for medical image segmentation; however, the algorithms become trapped in local minima and have low convergence speeds, particularly as the number of threshold levels increases. Consequently, in this paper, we develop a new multilevel thresholding image segmentation technique based on the jellyfish search algorithm (JSA) (an optimizer). We modify the JSA to prevent descents into local minima, and we accelerate convergence toward optimal solutions. The improvement is achieved by applying two novel strategies: Ranking-based updating and an adaptive method. Ranking-based updating is used to replace undesirable solutions with other solutions generated by a novel updating scheme that improves the qualities of the removed solutions. We develop a new adaptive strategy to exploit the ability of the JSA to find a best-so-far solution; we allow a small amount of exploration to avoid descents into local minima. The two strategies are integrated with the JSA to produce an improved JSA (IJSA) that optimally thresholds brain MR images. To compare the performances of the IJSA and JSA, seven brain MR images were segmented at threshold levels of 3, 4, 5, 6, 7, 8, 10, 15, 20, 25, and 30. IJSA was compared with several other recent image segmentation algorithms, including the improved and standard marine predator algorithms, the modified salp and standard salp swarm algorithms, the equilibrium optimizer, and the standard JSA in terms of fitness, the Structured Similarity Index Metric (SSIM), the peak signal-to-noise ratio (PSNR), the standard deviation (SD), and the Features Similarity Index Metric (FSIM). The experimental outcomes and the Wilcoxon rank-sum test demonstrate the superiority of the proposed algorithm in terms of the FSIM, the PSNR, the objective values, and the SD; in terms of the SSIM, IJSA was competitive with the others. 相似文献
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遥感影像的水库水体信息提取对水库面积变化监测有很大的帮助,因此,提出一种基于遗传算法和改进Otsu算法的水体提取方法。对处理后的遥感影像使用NDWI (normalized difference water index)水体指数法进行初始的水体提取,由于传统的Otsu算法对直方图呈现双峰分布的图像提取效果不佳,利用遗传算法对最大类间方差公式进行双阈值计算,引入滑动窗口对图像进行阈值判断;使用自适应阈值算法进行局部阈值分割。通过对石梁河水库和小塔山水库的实验,表明该方法能够准确提取出水库的水体信息,误提取和漏提取现象得到了很大的改善。 相似文献
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冯芝丽 《网络安全技术与应用》2013,(8):50-51
二维Otsu图像分割算法将类间离散度矩阵的迹作为阈值识别函数,计算复杂度高且易导致分割错误,为此对二维Otsu算法进行改进,设计一种新的阈值识别函数.通过对比试验验证改进算法的有效性. 相似文献
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基于分解的灰度图像二维阈值选取算法 总被引:12,自引:0,他引:12
作为一维Otsu法的推广, 二维Otsu法综合考虑了像素点的灰度信息及其邻域灰度的均值信息, 可以有效地滤除噪声. 其快速算法采用递归的方式构建查找表, 将算法的时间复杂性由OL4降到OL2. 提出基于分解的阈值选取算法, 求解两个一维Otsu法的阈值来替代原始的二维Otsu法的最佳阈值. 指出在原算法的假设成立的条件下, 该方法可以得到与原二维Otsu法相同的分割阈值, 而算法的时间复杂性可以进一步降低到OL. 而在实际中, 原算法的假设一般不成立. 本文的实验结果表明此时该阈值选取方法也可以在保证原二维Otsu算法良好的抗噪性的前提下, 计算阈值所需的时间更短、空间更小, 且阈值化结果也可以达到或优于二维Otsu算法的结果. 相似文献
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阈值法分割图像时只利用图像的灰度信息,具有直观、实现简单的特点。针对传统的粒子群优化算法(Particle Swarm Optimization,PSO)分割图像易陷入局部最优的缺点,提出一种基于改进粒子群优化算法的Otsu图像阈值分割方法。以Otsu算法的类间方差作为适应度函数,在每次迭代中选取适应度较好的粒子同时加入新的粒子,以提高粒子多样性。实验表明,与Otsu算法和PSO算法相比,改进的粒子群优化算法不仅加快了收敛速度和运算速度,而且提高了图像分割的准确率。 相似文献
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针对传统的分数阶微分应用于图像增强中会在强化图像边缘的时候忽视了图像的纹理,或者在保留更多图像纹理的同时弱化了图像边缘等不足,本文提出一种可以根据像素点的动态梯度来自适应调整分数阶微分阶次的图像增强新方法.该方法引入改进的二维Otsu准则,并结合图像的区域特征构造出自适应分数阶微分函数,进而求出与每一个像素点相对应的分数阶微分阶次.最后,实验结果表明该方法比较现有的方法可以更好的提取和增强图像边缘的同时,保留图像弱纹理和平滑区域,从而达到更佳的图像增强效果. 相似文献
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