基于改进遗传算法的自动阈值图像分割方法

图像分割法在图像分割的过程中只考虑象素的灰度值,没有考虑空间特性和存在计算复杂性过大的缺陷,影响图像效果.针对上述问题,提出一种基于改进遗传算法的自动阈值图像分割算法.方法对遗传算法中的编码办式、交叉算子、变异算子等参数进行了一些适当改进.把图像分割最佳阈值选取转换成优化问题.利用改进遗传算法的寻优高效性求解最佳阈值,实现图像分割.仿真结果证明,新算法极大地缩短了寻优时间,增强了图像分割过程中的抗噪性能,提高了图像分割的效率.从而有利于计算机视觉的后续处理,可以实现实时图像分割,具有实用价值.     

在线钢坯喷号自动视觉检测系统设计

以在线生产的热钢坯标号为识别对象,设计了一套实时视觉检测系统.利用灰度面积滤波、改进Marr边缘提取算子、自动阈值等图像处理技术滤除干扰,完成字符提取;通过投影法得到单个字符;并且引入距离变换的思想对模板匹配法进行改进,能更加准确地识别标号.视觉系统还利用无线技术进行数据传输.实验结果表明该检测系统是有效可行的,在识别准确率上近98%,每块钢坯的识别时间约1.5 s,能满足生产线需要.     

基于改进边缘检测的视觉注意计算模型

本文主要针对传统Itti视觉注意计算模型,引入边缘特征信息,优化视觉注意计算模型.在引入边缘特征信息的过程中,本文对Canny边缘检测算法进行改进：以改进后的双边滤波算法代替高斯滤波从而更好的保持边缘,借鉴Sobel算子从4个方向计算梯度幅值来代替原方法中的从2个方向来计算的过程,利用改进的OTSU算法选取双阈值代替手动设置阈值,从而降低图像分割时的误检、漏检现象.在实验中,我们发现,该方法相较于建立在普通Canny算法基础上的Itti视觉注意计算模型,对显著区域的提取效果上有很大的提高.     

一种遗传优化和Ostu的图像模糊边缘特征提取方法

边缘检测是图像预处理的重要内容之一,在对Pal和King经典模糊边缘检测算法改进的基础上,提出了一种基于遗传算法和Otsu进行图像阈值选取,以不同阈值为基准确定出线性隶属函数,对多峰图像确定多阈值隶属函数的方法,进行模糊增强,从而提取边缘,实验结果表明该算法不仅提高了边缘提取质量,而且缩短了阈值选取时间,是一种有效性、正确性的图像处理方法。     

脐橙图像分割中阈值的选取研究及实现

图像分割是计算机视觉领域的一个重要而且基本的问题。本文提出了一套完整的脐橙图像分割算法,其采用改进的遗传算法结合改进的阈值分割方法。通过仿真实验,本文所提出的算法得出的阈值范围更加稳定,而且对分割图像的边缘处理得更细致。     

改进的Otsu理论在图像阈值选取中的应用

提出了一种基于GA优化的Otsu理论进行图像阈值选取的新方法.利用传统的Otsu理论进行图像阈值选取,计算量较大,准则函数不一定单峰,不适于最佳阈值的求取.遗传算法理论为一种全局搜索方法,它自适应地控制搜索过程以求得最优解,从而可克服Otsu方法的不足,有利于计算机视觉的后续处理.文中将遗传算法和Otsu理论进行了有机结合,实现了图像阈值自动选取,且大大降低了计算量.实验结果表明该算法不仅提高了分割质量,而且缩短了寻优时间,从而说明了该算法的有效性、正确性.基于改进Otsu优化的模糊算子理论的提出,解决了模糊算子中关键参数确定困难的问题,实现了其参数的自适应获取,并将该理论应用于图像增强中,从而有效地消除了图像的模糊和噪声干扰.     

一种改进型边缘检测的混合量子遗传算法

图像边缘包含非常重要的图像信息,针对图像处理中的模糊边缘检测存在的缺陷,将免疫学中的克隆选择理论引入量子遗传算法,利用这种新的混合量子遗传算法对图像阈值进行优化得到最佳阈值,改进模糊边缘的检测算法。通过测试图像的边缘检测结果表明,该算法具有较好的检测模糊边缘和抑制噪声能力,用于边缘检测能获得良好的效果。     

基于GCV准则与Otsu法的Canny算子研究

为了增强图像的可读性,解决因光照、噪声等因素造成的图像模糊、边缘不清等问题,在前人研究的基础上提出了对Canny算子的改进.用遗传算法对基于GCV准则的阈值函数自动寻优,在降低噪声的同时增强了图像的可读性;用评价函数对Otsu法自适应设定高低阈值,无需考虑阈值比例,减少了伪边缘现象.不同图像的边缘提取实验和数据分析表明,该方法在检测精度、抗噪能力和运算效率等方面都得到明显提高.对于存在的不足提出了进一步研究方向.     

基于整体变分图象恢复模型的小波域正则化方法

通过改进小波软阈值收缩的过程,提出了小波框架下的整体变分正则化模型.模型中利用改进小波阈值技术选取合适的需要保留的小波系数,然后对该系数重建图象进行空域各向异性扩散处理.文中提出了该变分问题完整的空域和小波域交替迭代的图象恢复算法.实验证明,该算法不仅具有较强的噪声抑制能力,而且能够保持和增强图象的边缘,大大提高了图象的视觉质量.     

基于改进遗传算法的图像分割

将改进遗传算法用于图像分割,利用判断分析法和最佳熵自动阈值法两种阈值分割方法进行实验并加以比较,结果表明,利用最佳熵自动阈值法进行的图像分割优于判断分析法.     

On searching for an optimal threshold for morphological image segmentation

Segmentation of images represents the first step in many of the tasks that pattern recognition or computer vision has to deal with. Therefore, the main goal of our paper is to describe a new method for image segmentation, taking into account some Mathematical Morphology operations and an adaptively updated threshold, what we call Morphological Gradient Threshold, to obtain the optimal segmentation. The key factor in our work is the calculation of the distance between the segmented image and the ideal segmentation. Experimental results show that the optimal threshold is obtained when the Morphological Gradient Threshold is around the 70% of the maximum value of the gradient. This threshold could be computed, for any new image captured by the vision system, using a properly designed binary metrics.     

Genetic algorithm-based strategy for identifying association rules without specifying actual minimum support

We design a genetic algorithm-based strategy for identifying association rules without specifying actual minimum support. In this approach, an elaborate encoding method is developed, and the relative confidence is used as the fitness function. With genetic algorithm, a global search can be performed and system automation is implemented, because our model does not require the user-specified threshold of minimum support. Furthermore, we expand this strategy to cover quantitative association rule discovery. For efficiency, we design a generalized FP-tree to implement this algorithm. We experimentally evaluate our approach, and demonstrate that our algorithms significantly reduce the computation costs and generate interesting association rules only.     

Multi-modal function optimization with the ZEDS (zoomed evolutionary dual strategy) algorithmzoomed evolutionary algorithm

This article introduces a new evolutionary algorithm for multi-modal function optimization called ZEDS (zoomed evolutionary dual strategy). ZEDS employs a two-step, zoomed (global to local), evolutionary approach. In the first (global) step, an improved ‘GT algorithm’ is employed to perform a global recombinatory search that divides the search space into niches according to the positions of its approximate solutions. In the second (local) step, a ‘niche evolutionary strategy’ performs a local search in the niches obtained from the first step, which is repeated until acceptable solutions are found. The ZEDS algorithm was applied to some challenging problems with good results, as shown in this article.     

Genetic algorithms (GAs) to evolve multiple-agent cooperative systems

In this paper, a microrobot soccer-playing game, such as that of MIROSOT (Microrobot World Cup Soccer Tournament), is adopted as a standard test bed for research on multiple-agent cooperative systems. It is considerably complex and requires expertise in several difficult research topics, such as mobile microrobot design, motor control, sensor technology, intelligent strategy planning, etc., to build up a complete system to play the game. In addition, because it is an antagonistic game, it appears ideal to test whether one method is better than other. To date there have been two different kinds of architecture for building such system. One is called vision-based or centralized architecture, and the other is known as robot-based or decentralized architecture. The main difference between them lies in whether there exists a host computer system which responds to data processing and strategy planning, and a global vision system which can view the whole playground and transfer the environment information to the host computer in real time. We believe that the decentralized approach is more advanced, but in the preliminary step of our study, we used the centralized approach because it can lighten any overload of the microrobot design. In this paper, a simplified layer model of the multiple-agent cooperative system is first proposed. Based on such a model, a system for a microrobot soccer-playing game is organized. At the same time a simple genetic algorithm (SGA) is used for the autonomous evolution of cooperative behavior among microrobots. Finally, a computer simulation system is introduced and some simulated results are explained. This work was presented, in part, at the Third International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–21, 1998.     

Implementation of a 3D Vision System on DSPs TMS320C31

In this paper, the implementation of a new stereo vision process on a specialized architecture which comprises of three DSPs TMS320C31 is described. The first step of our stereo vision system is a self-adaptive image segmentation algorithm based on a new concept that we call declivity. The second step is a new and fast stereo matching algorithm based on dynamic programming and using self-adaptive decision parameters. The goal of our work is to develop a stereo vision system that achieves an acceptable level of performance using a modest amount of hardware. This implementation is organized as follows: declivity extraction from the two stereo images is performed in parallel on two DSPs, one for the right image and the other for the left one. Then, the last DSP computes the declivity matching based on our dynamic programming method as well as the 3D maps calculation. Finally, experimental results obtained using real pairs of stereo images on a VME 150/40 Imaging Technology Vision System are presented. They show the feasibility and the effectiveness of our system. These results can surely be improved by using a new generation of DSP in order to consider real-time applications.     

Automatic annotation of tennis games: An integration of audio,vision, and learning

Fully automatic annotation of tennis game using broadcast video is a task with a great potential but with enormous challenges. In this paper we describe our approach to this task, which integrates computer vision, machine listening, and machine learning. At the low level processing, we improve upon our previously proposed state-of-the-art tennis ball tracking algorithm and employ audio signal processing techniques to detect key events and construct features for classifying the events. At high level analysis, we model event classification as a sequence labelling problem, and investigate four machine learning techniques using simulated event sequences. Finally, we evaluate our proposed approach on three real world tennis games, and discuss the interplay between audio, vision and learning. To the best of our knowledge, our system is the only one that can annotate tennis game at such a detailed level.     

Fundamental limits of Bayesian inference: order parameters andphase transitions for road tracking

There is a growing interest in formulating vision problems in terms of Bayesian inference and, in particular, the maximum a posteriori (MAP) estimator. In this paper, we consider the special case of detecting roads from aerial images and demonstrate that analysis of this ensemble enables us to determine fundamental bounds on the performance of the MAP estimate. We demonstrate that there is a phase transition at a critical value of the order parameter; below this phase transition, it is impossible to detect the road by any algorithm. We derive closely related order parameters which determine the time and memory complexity of search and the accuracy of the solution using the n* search strategy. Our approach can be applied to other vision problems, and we briefly summarize the results when the model uses the “wrong prior”. We comment on how our work relates to studies of the complexity of visual search and the critical behaviour in the computational cost of solving NP-complete problems     

多传感器信息融合的服务机器人导航方法

在机器人中,计算机视觉与传感器开始交融.本文设计了以人脸识别为视觉导引的主体,传感器为辅的服务机器人系统,提出了一种基于视觉的图像处理算法,采用将形态学处理与自适应阈值分割相结合直接除掉阴影,使用多传感器与视觉融合的方法来解决视觉误判的问题.在小车避障中运用单目测距的原理,跳过了传统相机的标定问题,并将该算法与迷宫机器人路径规划中的左手法则相结合运用在设计的服务机器人中.     

Billiard Combat Modeling and Simulation Based on Optimal Cue Placement Control and Strategic Planning

The selection of a best sequential shots for a given start cue position is a major challenging task in a billiard game. A new algorithm is proposed as a strategy to apply maximum tolerance angle search sequentially. The strategy considers combinations among all pockets and target object balls during both the pre and post collision shots selection processes. A simulation program is developed to test the strategy in a competition scenario by players with different proficiencies. The level of proficiency of players in the competition is controlled by a threshold value as a criterion to evaluate capability to conduct consecutive shots and when to give out right of play. The winning score of each game (win rate) is used as a performance comparison index among different gaming situations and to verify the effectiveness of the algorithm. The initial results of several simulation games using our strategy show that higher proficiency player can out beat lower proficiency player easily. This is consistent with the gaming situation in the real world, showing the consistency of our simulation program. The simulation also verifies that the play order does decide the final competition outcomes, when the players?? proficiencies are close to each other. This work is the first to investigate the effects of consecutive shots and order of play on the billiard gaming results. A low cost training system is proposed to verify the efficiency of the repositioning algorithm in real world settings. The system adapts an augmented reality technology to instruct users for reliable aiming assistance. It makes use of a vision system for cue ball, object ball locations and cue stick velocity tracking. In all, the simulation program can provide an initial proof of the effectiveness of the reposition algorithm in the competition situation. Experiments results of maximum tolerance angle all pocket search strategy using our training facility as tested by users with different skill levels all out performed the results without guidance for the set of users with the same proficiency.