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Algorithm of Binary Image Labeling and Parameter Extracting Based on FPGA

机译:基于FPGA的二值图像标注与参数提取算法

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For the real-time detection and identification requirements of the rail profile image,A quickly algorithm using connectivity labeling of binary image and parameter extracting to remove the speckle disturbing was presented in this paper,based on FPGA,it can use the limited hardware resources of the system to realize high-speed and accurate binary image labeling and feature extraction,obtain the bright band image and region. This method overcomes the shortcoming of previous methods which must scan pixel repeated and require a large memory to record the relationship of the connected components,and a large computation to merge the labeling. Also,it is rapid,simple, rules,and extensibility,the processing speed will be increased by providing a quick effective way to identify and record the complex relationship between regions,and by completing the label merge or parameter extraction during the line or field blanking. realizing of FPGA can accurately and effectively identify the complex connectivity between images,produce the correct label results and extract the characteristic parameters of each connected component which can limit the subsequent processing in a rectangle and save the time and resource greatly,provide guarantee for subsequent identification. The algorithm is used and we have a good effect on the scene testing of rail measurement,it is enough to meet the requirement of real-time image recognition system.
机译:针对铁路轮廓图像的实时检测和识别要求,提出了一种基于FPGA的二进制图像连通性标记和参数提取快速消除斑点干扰的算法,该算法可以利用有限的硬件资源。该系统实现了高速准确的二值图像标注和特征提取,获得了亮带图像和区域。该方法克服了先前方法的缺点,该方法必须重复扫描像素并且需要大的存储器来记录所连接的组件的关系,并且需要大量的计算来合并标记。而且,它快速,简单,规则和可扩展,通过提供一种快速有效的方法来识别和记录区域之间的复杂关系,并在行或字段消隐期间完成标签合并或参数提取,将提高处理速度。 。 FPGA的实现可以准确,有效地识别图像之间的复杂连通性,产生正确的标签结果并提取每个连接组件的特征参数,从而将后续处理限制在一个矩形内,大大节省了时间和资源,为后续的识别提供了保证。该算法的使用对轨道测量的现场测试有很好的效果,足以满足实时图像识别系统的要求。

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