自适应阈值图像二值化及形态学处理的FPGA实现
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1. 上海理工大学光电信息与计算机工程学院上海200093; 2. 中国科学院上海技术物理研究所上海200083

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TP391.4

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国家自然科学基金青年基金(61302181)、上海市闵行区产学研合作计划(3714302006)、上海市教委创新项目(13YZ111)资助


Adaptive threshold binarization and morphological image processing based on FPGA
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1. School of OpticalElectrical and computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China; 2. Shanghai Institute of Technical Physics of Chinese Academy of Sciences, Shanghai 200083, China

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    摘要:

    针对固定阈值法图像二值化不足以及二值化后图像存在严重干扰,传统DSP等处理器在高速图像处理中实时性差,提出了以FPGA/Nios II为处理器,运用改进的自适应阈值Sobel算法实现对图像的二值化,再进行形态学的处理。整个系统实现包括原始图像的采集、色彩格式转换、灰度处理、边缘检测以及运用中值滤波和加权平均法实现自适应阈值图像二值化,最后再运用形态学方法对二值化后图像做进一步处理,实现轮廓的更加有效的提取,并通过VGA接口实现显示。实验结果表明该系统检测效率高,速度快,稳定可靠。

    Abstract:

    For reducing a fixed threshold binarization method’s drawback and the serious Inadequate and Interference after binarization handling,meanwhile the traditional DSP and other processors in highspeed image processing in realtime poor is not good enough, proposing that using FPGA / Nios II processor and the improved adaptive threshold Sobel algorithm for image binarization, morphological processing again. The whole system implementation includes the original image capture, color format conversion, gradation processing, edge detection and median filtering using the weighted average method and adaptive threshold image binarization, and finally by using morphological methods to further deal with the binary image, to achieve a more efficient extraction of contour, and through VGA interface display. Experimental results show that the system is high efficient, fast, stable and reliable.

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陈鑫元,李筠,杨海马,宋佳,邵璐先.自适应阈值图像二值化及形态学处理的FPGA实现[J].电子测量技术,2016,39(7):67-71

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  • 在线发布日期: 2016-08-17
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