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Search Results: 1 - 10 of 313168 matches for " range image registration<br>遗传算法 "
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Range image registration using hybrid genetic algorithm and point to plane distance based measure

GAO Peng dong,PENG Xiang,LI A meng,LIU Xiao li,

计算机应用研究 , 2007,
Abstract: This paper presented a novel approach for precise registration of range images pair with an improved genetic algorithm(GA) and a new error metric based on the point to plane distance. Different to the existed ICP methods, this approach formulated the surface registration as a high dimensional optimization problem. Then combined the strategy of simulated annealing(SA) selection, hill climbing and dynamic parametric space degeneration into a GA to offer much faster convergence and more precise registration. At the same time, employed a new measure based on the point to plane distance as fitness function to evaluate the alignment error, which made the approach more robust. A number of experiments demonstrate that the presented method is insensitive to noises as well as the initial pose estimation and has high precision and fast convergence.
Study of Registration of Infrared Thermal Wave Images Based on Genetic Algorithm


红外 , 2010,
Abstract: Because the angle of field of view of an infrared thermal imager is limited and higher resolution is required for the obtained thermal wave image, the thermal wave nondestructive detection of a large object can be implemented only when several images are jointed. For the joint of images, the premise is that the images should be registered precisely. According to the concept of template matching, the Genetic Algorithm (GA) is incorporated into the infrared thermal wave image registration. Through the modification of selection strategy, an adaptive crossover and mutation probability is designed to realize precise registration of thermal images. The experimental result shows that the method can realize the precise registration of thermal images and its operation speed and stability are improved.
Local Registration of Medical Images Using Feature Point and Intensity Information

PENG Wen,TONG Ruo-feng,QIAN Gui-ping,DONG Jin-xiang,

中国图象图形学报 , 2008,
Abstract: A local image registration method is proposed specially for the conditions when images, in medical image registration, are largely similar or the differences are not significant. The transformation function is a radial basis function with compact support and its locality can be conveniently controlled by distributing the feature points into the desired regions, which especially allows us to deal with local changes in medical images. Mutual information is chosen as cost function in order that the transformation function can be achieved accurately. In the process of the optimization, the image registration is treated as optimal problem and niche genetic algorithm is employed to optimize the transformation function parameters because it can overcome the drawbacks of premature and weak exploitation capabilities compared with genetic algorithm. The experiments on the simulated image with the known transformation function and the real image are conducted by using the proposed method. The results show that the optimal transformation function can be found and its action domain is controlled within a relatively small region. The presented method, which is a feasible and robust medical image registration approach, exploits the advantages of both feature points and intensity information and can obtain the accurate transformation function by the efficient optimization strategy.
Optical Image and SAR Image Registration Via Implicit Similarity

LI Meng-jun,LI Zhi-yong,CHEN Tian-ze,

中国图象图形学报 , 2009,
Abstract: 异质图像配准是多源图像融合的关键步骤之一,通常需要精确提取和匹配图像的同名特征,这种同名特征在成像机理差异巨大的光学和SAR图像中进行提取和匹配十分困难,利用相同场景图像中的隐含相似性可以有效避开这一难点.为了对光学和SAR图像进行配准,提出了一种基于隐含相似性的光学和SAR图像配准方法,该算法首先选用高梯度幅值像素作为隐含特征点集,然后通过像素迁移来构建相似测度准则函数,并用遗传算法对准则函数解空间进行全局优化搜索来获取配准解,这样就将图像配准问题归于模型参数优化求解过程.实验结果表明,该方法有效可行,配准图像能达到像素级配准精度.
Edge detection of range images using genetic neural networks
FAN Jian-ying DU Ying ZHOU Yang WANG Yang,
FAN Jianying
,DU Ying,ZHOU Yang,WANG Yang

重庆邮电大学学报(自然科学版) , 2009,
Abstract: Due to the complexity and asymmetrical illumination, the images of object are difficult to be effectively segmented by some routine method. In this paper, a kind of edge detection method based on image features and genetic algorithms neural network for range images was proposed. Fully considering the essential difference between an edge point and a noise point, some characteristic parameters were extracted from range maps as the input nodes of the network in the algorithm. Firstly, a genetic neural network was designed and implemented. The neural network is trained by genetic algorithm, and then genetic neural network algorithm is combined with the virtue of global optimization of genetic algorithm and the virtue of parallel computation of neural network, so that this algorithm is of good global property. The experimental results show that this method can get much faster and more accurate detection results than the classical differential algorithm, and has better anti-noise performance.
Matching Optical Image to SAR Image Using Nonlinear Equation and Hausdorff Distance

Wang Zi-lu,Li Zhi-yong,Su Yi,
,李智勇,粟 毅

电子与信息学报 , 2009,
Abstract: This paper describes a new method for matching SAR image and optical image. First, regularizing anisotropic heat diffusion equations is used for segmenting closed-boundary regions in SAR image. After superposing the center of mass of closed-boundary regions, Haudorff distance and genetic algorithm are used to determine scaling and rotation parameters respectively. Finally, the affine-transformed result is refined by binary image correlation to achieve high precise registration. Experimental results indicated that this method can perform automatic registration under precision acquirement for images which differ by translation, rotation and scaling.
New genetic algorithm for image restoration

ZHU Ce,YANG Xiao-fan,CHEN Jing,TANG Rong-wang,CHEN Guo,

计算机应用 , 2006,
Abstract: A new genetic algorithm for image restoration was presented by incorporating new chromosome coding method and simulated annealing. Experimental results justify our algorithm has better quality of the restored image and lower computational complexity.
The Study of Remote Sensing Images Matching Method Based on Wavelet Transform and Genetic Algorithms

Xu Jian-bin,Hong Wen,Wu Yi-rong,

电子与信息学报 , 2005,
Abstract: In this paper, a matching method based on wavelet transform and genetic algorithms is proposed. First, the reference images and target images are decomposed to low resolution images using wavelet transform. Then, genetic algorithms, which are useful in finding global optima, are used to match the lowest resolution images. Based on the matching result, the matching between the higher resolution images can be implemented stepwise up to the full resolution images. The results confirm the proposed algorithm can improve the efficiency greatly while guarantee the accuracy.
A Remote Sensing Images Matching Method Based on Zernike Moments and Steady Genetic Algorithms

Xu Jian-bin,Hong Wen,Wu Yi-rong,

电子与信息学报 , 2005,
Abstract: In this paper, a remote sensing images matching method based on Zernike moments and steady genetic algorithms is proposed. Genetic algorithms, which are rapid and efficient in global finding optima, are used to match the images. Considering rotation distortion, the Zernike moments of remote sensing images are used as similarity measurements. The results confirm the proposed algorithm can overcome the distortion of images and improve the efficiency while guarantee the accuracy.
Image Segmentation Method Using Genetic Algorithms of Multiple Parameters

Wu Chengke,Liu Jing,Hou Gexian,

自动化学报 , 1998,
Abstract: 图像分割的多参量遗传算法吴成柯刘靖侯格贤(西安电子科技大学信息工程系西安710071)关键词遗传算法,图像分割.1)国防预研基金资助课题.收稿日期1995-11-061引言图像分割是计算机视觉研究中一个重要而困难的任务.虽然图像分割一直受到研究人员的...
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