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汽车数量的不断增长使交通变得日益拥堵,已经严重的影响了我们的生活。在这种背景下,人们开始致力于智能交通系统的研究,作为该系统的核心部分,车牌自动识别技术取得了较快的发展,并且在其他领域中也发挥了很大的作用。本文重点讨论了车牌定位部分。 相似文献
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汽车车牌自动识别是智能交通管理的重要部分,对管理和监控车辆有重要作用.提出了一种车牌自动识别算法.首先提取摄像头拍摄到的车辆照片,对图片进行灰度化、图像降噪、二值化等预处理,然后对车牌号码进行定位、分割和归一化,再根据字符的特征用多级分类器对车牌号逐级分类,最后用模板匹配法对车牌号码进行识别,这种方法计算量低,准确度高... 相似文献
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车牌识别是智能交通的一个重要组成部分,系统一般包括车牌定位,字符分割和字符识别。对目前车牌识别领域的各种算法进行分析,总结和改进。实验结果表明,所提方法能快速有效的获取车牌信息。 相似文献
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复杂背景下基于HSV空间和模板匹配的车牌识别方法研究 总被引:1,自引:0,他引:1
车牌识别技术作为交通管理自动化的重要手段,在交通监视和控制中占有很重要的地位.车牌识别过程可分为车牌定位、车牌校正、字符分割和字符识别四个部分.在车牌定位中,若单纯采用纹理特征或颜色特征来进行定位,往往适用于背景较为简单的场景,对复杂背景的定位效果尚有待改进.在字符分割中,目前单行车牌的分割已比较成熟,但双行车牌的分割仍不理想.提出一种在HSV空间下两次颜色标定和纹理特征相结合的定位方法和一种单双行车牌的字符分割方法.该定位方法利用车牌固定颜色搭配特性,对图片两次标记并利用投影法定位车牌,对200张不同背景图片测试,定位准确率达到98%.在字符分割部分,利用改进的模板匹配方法对字符分割,可适用于单、双行车牌分割,准确率达到95%. 相似文献
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针对车牌的分割,提出一种基于马尔可夫随机场(Markov random field)模型建立车牌的分割模型,通过置信度传播(Belief Propagation)算法对分割模型进行迭代推理,得到车牌的分割目标。实验结果表明提出算法的有效性。 相似文献
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随着高速公路里程的不断增加,尤其是高速公路联网收费范围的不断扩大,如何利用高新科技,进一步提高高速公路管理及服务水平,使道路使用者体会到安全、舒适和高效,日益成为大家关注的问题。 相似文献
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车辆牌照自动识别是智能交通管理系统中的关键技术。本文总结了目前汽车牌照识别系统的发展现状和存在的问题,分别从车牌定位、区域分割、字符识别这几个关键步骤以不同的理论角度对近年来国内外出现的车牌识别系统方法进行了综述。最后对车辆牌照识别系统进行了总结并提出今后一些研究方向。 相似文献
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交通车辆的自动车牌识别系统由于其广泛的商业应用,是一项具有挑战的研究领域。第一步同时也是非常重要的就是把从摄像机捕获的图像进行车牌定位。在车牌定位和车牌数字识别方面,大量的文献讨论这个问题。然而,其中的人大多数只限于特定的环境。例如场景不是很昏暗、背景不是很复杂等等。目前,研究的车牌定位系统,是基于新型的多阶段的方法,通过对比拉伸的灰度图像的垂直边缘梯度进行分析,实验证明这种方法对于89.2%的车牌有效。 相似文献
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With the social and economic development and the improvement of people's living standards, smart medical care is booming, and medical image processing is becoming more and more popular in research, of which brain tumor segmentation is an important branch of medical image processing. However, the manual segmentation method of brain tumors requires a lot of time and effort from the doctor and has a great impact on the treatment of patients. In order to solve this problem, we propose a DO-UNet model for magnetic resonance imaging brain tumor image segmentation based on attention mechanism and multi-scale feature fusion to realize fully automatic segmentation of brain tumors. Firstly, we replace the convolution blocks in the original U-Net model with the residual modules to prevent the gradient disappearing. Secondly, the multi-scale feature fusion is added to the skip connection of U-Net to fuse the low-level features and high-level features more effectively. In addition, in the decoding stage, we add an attention mechanism to increase the weight of effective information and avoid information redundancy. Finally, we replace the traditional convolution in the model with DO-Conv to speed up the network training and improve the segmentation accuracy. In order to evaluate the model, we used the BraTS2018, BraTS2019, and BraTS2020 datasets to train the improved model and validate it online, respectively. Experimental results show that the DO-UNet model can effectively improve the accuracy of brain tumor segmentation and has good segmentation performance. 相似文献
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手背静脉图像的采集过程中,由于图像采集设备、光照、皮下脂肪厚度等因素的影响,手背静脉图像的对比度比较低,同时图像噪声严重影响静脉提取。针对此问题,本文提出了一种基于静脉灰度值特征的图像分割与对比度增强算法。首先提取ROI(有效的感兴趣区域)和对ROI进行维纳滤波;然后采用新的图像分割算法对静脉图像进行静脉提取,利用8-邻接内边界跟踪方法和形态学处理方法对静脉二值图像进行去噪;最后将ROI与去噪后的图像进行加权叠加得到对比度增强的静脉图像。实验结果表明,通过采用基于静脉灰度值特征的图像分割算法可以很好地获取到静脉脉络,最终可以获得高对比度的静脉图像。 相似文献
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To segment vascular structures in 3‐D CTA/MRA images, this article presents a new region growing algorithm based on local cube tracking. In the proposed algorithm, a small local cube is segmented to detect a vessel segment, and the following local cube(s) is determined based on the segmentation result. This procedure is repeated until the segmentation is completed. By confining the segmentation inside each local cube, a robust result can be obtained even in a tubular structure of steadily changing intensity. For segmentation, a locally adaptive and competitive region growing scheme is adopted to obtain well‐defined vessel boundaries. It should be emphasized that the proposed algorithm can detect all branches with practically acceptable computational complexity. In addition, its segmentation result is represented as a tree structure having many branches so that a user may easily correct the result branch‐by‐branch, if necessary. Experimental results from real images prove that the proposed algorithm produces prospective vessel segmentation results for 3‐D CTA/MRA images and segments vessels of various sizes well, including stenoses and aneurysms. © 2003 Wiley Periodicals, Inc. Int J Imaging Syst Technol 13, 208–214, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.10059 相似文献
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用于彩色图像分割的改进遗传FCM算法 总被引:4,自引:0,他引:4
本文提出了一种适用于彩色图像分割的遗传模糊C均值聚类(GAFCM)算法.该算法使用Ohta等人提出的彩色特征集中的第一个分量作为图像像素的一维特征向量,并利用由像素空间到特征空间的映射来改进目标函数,从而大大降低了运算量;使用对特征空间结构没有特殊要求的特征距离代替欧氏距离,从而克服了特征空间结构对聚类结果的影响;使用引入FCM优化的遗传算法来搜索最优解,从而提高了搜索速度.实验表明,该算法不但能很好地分割彩色图像,而且具有运算量小、收敛速度快的优点. 相似文献
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In Japan, a driving lesson consisting of a lecture, a driver aptitude test, on-road driving assessment and a discussion session was added to the driving license renewal procedure for drivers aged 75 years or older in 1998 and for drivers aged 70 years or older in 2002. We investigated whether these additions contributed to a reduction in at-fault motor vehicle collisions (MVCs) by examining the trend of the at-fault MVC rates per licensed driver and the rate ratios of the older drivers relative to those aged 65–69 years for the years 1986–2011. All data were derived from nationwide traffic statistics. If the introduction of the lesson was effective in reducing at-fault MVCs of older drivers, the rate ratio should have declined, given that the lesson targeted only the older drivers. We found this was not the case, i.e., there was no declining trend in the at-fault MVC rate ratios of both drivers aged 75 years or older and drivers aged 70 years or older, relative to drivers aged 65–69 years, after the driving lesson at license renewal became mandatory for these older drivers. Therefore, the mandatory lesson for the older drivers at license renewal needs to be reconsidered. 相似文献
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为了克服传统分水岭算法引起的过分割问题,提出了一种基于简单线性迭代聚类(SLIC)与分水岭算法相结合的彩色图像分割算法,以获得更理想的分割效果。该算法首先利用图像复杂度计算预分割的超像素个数,并利用SLIC对原始图像进行超像素分割预处理,以减少后续处理中的冗余信息;然后,提出了一种自适应计算阈值的方法对预处理图像的梯度图像进行阈值处理,以有效去除噪声,获得较完整的轮廓信息;最后,利用分水岭分割算法对进行极小值标记提取后的图像进行分割。通过对大量图片进行实验表明,本文算法可以有效地抑制传统分水岭算法所产生的过分割问题,在LCE和GCE的对比上优于传统算法,分割质量有所提高。 相似文献
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一种适合于多目标检测的图像分割方法 总被引:14,自引:2,他引:14
提出一种适合于多目标检测的8邻域图像分割方法,用以获取目标特征量,准确分割图像。在对二值化图像扫描形成目标块的过程中,标记各个目标像素,记录目标的边界点,得出分割目标的面积、周长、质心坐标。利用这些信息,可以选择跟踪一个或多个目标。仿真结果证明了该方法实用可行。 相似文献