The concept and advantage of reconfigurable technology is introduced. A kind of processor architecture of re configurable macro processor (RMP) model based on FPGA array and DSP is put forward and has been implemented...The concept and advantage of reconfigurable technology is introduced. A kind of processor architecture of re configurable macro processor (RMP) model based on FPGA array and DSP is put forward and has been implemented. Two image algorithms are developed: template-based automatic target recognition and zone labeling. One is estimating for motion direction in the infrared image background, another is line picking-up algorithm based on image zone labeling and phase grouping technique. It is a kind of 'hardware' function that can be called by the DSP in high-level algorithm. It is also a kind of hardware algorithm of the DSP. The results of experiments show the reconfigurable computing technology based on RMP is an ideal accelerating means to deal with the high-speed image processing tasks. High real time performance is obtained in our two applications on RMP.展开更多
A new algorithm is proposed to determine the actual length and the number of the protruding fibres of yarn based on a combination of image acquisition technology. First, a yarn hairiness image is obtained by the serie...A new algorithm is proposed to determine the actual length and the number of the protruding fibres of yarn based on a combination of image acquisition technology. First, a yarn hairiness image is obtained by the series of image processing procedures that include grayscale transformation,skew correction,yarn binary image acquisition and yarn core binary image obtaining. Then,the hairiness is realized in single pixel width by the usage of thinning algorithm. Finally, a baseline of yarn core margin is obtained,and pixels that match 8-neighbor template correctly are found by row scanning in a certain area. From this,these pixels are judged and the real crossover points of yarn core margin and hairiness,i. e.,the starting points of hairiness,are gained. The real length of the protruding fibres is calculated by tracking hairiness from the starting point constantly.展开更多
The following article has been retracted due to special reason of the authors. This paper published in Vol.5 No. 2, 2014, has been removed from this site. Title: Template Matching from 2-D into 1-D Author: Yasser
Template matching is a fundamental problem in pattern recognition, which has wide applications, especially in industrial inspection. In this paper, we propose a 1-D template matching algorithm which is an alternative ...Template matching is a fundamental problem in pattern recognition, which has wide applications, especially in industrial inspection. In this paper, we propose a 1-D template matching algorithm which is an alternative for 2-D full search block matching algorithms. Our approach consists of three steps. In the first step the images are converted from 2-D into 1-D by summing up the intensity values of the image in two directions horizontal and vertical. In the second step, the template matching is performed among 1-D vectors using the similarity function sum of square difference. Finally, the decision will be taken based on the value of similarity function. Transformation template image and sub-images in the source image from 2-D grey level information into 1-D information vector reduce the dimensionality of the data and accelerate the computations. Experimental results show that the computational time of the proposed approach is faster and performance is better than three basic template matching methods. Moreover, our approach is robust to detect the target object with changes of illumination in the template also when the Gaussian noise added to the source image.展开更多
针对库水位传统量测方法中水尺易锈蚀倾斜,精度低且成本高的问题,该文提出一种不依赖水尺,基于图像匹配的库水位变动识别方法。首先对监控相机拍摄的库坝上游面光学图像进行畸变消除和透视变换,消除相机误差。进一步选取包含水面的感兴...针对库水位传统量测方法中水尺易锈蚀倾斜,精度低且成本高的问题,该文提出一种不依赖水尺,基于图像匹配的库水位变动识别方法。首先对监控相机拍摄的库坝上游面光学图像进行畸变消除和透视变换,消除相机误差。进一步选取包含水面的感兴趣区域(region of interest,ROI)图像进行自适应二值化分割、形态学处理等前处理操作,将水面和库坝特征分离,突出水位线位置。最后,利用归一化互相关匹配算法(normalised cross correlation,NCC)对水位变动前后的两幅图像进行匹配计算,识别水位线变动距离。通过室内试验与现场测试验证上述方法实用性。结果表明:基于图像匹配的库水位动态识别方法可准确识别水位变动,相对误差约为5%,此算法鲁棒性较高。该研究可为库水位自动化、低成本监测提供一种新思路。展开更多
家用厨锅在制造时安装手柄需要焊接螺母座,针对螺母座焊接位置不准确的问题,设计了厨锅锅底标签角度测量系统。该测量系统通过搭建视觉采集平台采集图像,利用模板匹配原理对锅底图像进行角度检测。通过对不同种类锅底图像进行滤波、阈...家用厨锅在制造时安装手柄需要焊接螺母座,针对螺母座焊接位置不准确的问题,设计了厨锅锅底标签角度测量系统。该测量系统通过搭建视觉采集平台采集图像,利用模板匹配原理对锅底图像进行角度检测。通过对不同种类锅底图像进行滤波、阈值化与频域变换等图像处理算法制定感兴趣区域(ROI),由ROI依次创建形状模板;将采集到的图像经过预处理后根据已建好的同类模板进行匹配,匹配结果由Visual Studio 2019平台所建立的人机界面显示。实验表明,该测量系统平均误差可达0.08°,检出率达94%,平均检测时间0.35 s,明显优于传统的人工检测,能够满足工业的实际检测需求。展开更多
Template matching methods have been widely utilized to detect fabric defects in textile quality control. In this paper, a novel approach is proposed to design a flexible classifier for distinguishing flaws from twill ...Template matching methods have been widely utilized to detect fabric defects in textile quality control. In this paper, a novel approach is proposed to design a flexible classifier for distinguishing flaws from twill fabrics by statistically learning from the normal fabric texture. Statistical information of natural and normal texture of the fabric can be extracted via collecting and analyzing the gray image. On the basis of this, both judging threshold and template are acquired and updated adaptively in real-time according to the real textures of fabric, which promises more flexibility and universality. The algorithms are experimented with images of fault free and faulty textile samples.展开更多
文摘The concept and advantage of reconfigurable technology is introduced. A kind of processor architecture of re configurable macro processor (RMP) model based on FPGA array and DSP is put forward and has been implemented. Two image algorithms are developed: template-based automatic target recognition and zone labeling. One is estimating for motion direction in the infrared image background, another is line picking-up algorithm based on image zone labeling and phase grouping technique. It is a kind of 'hardware' function that can be called by the DSP in high-level algorithm. It is also a kind of hardware algorithm of the DSP. The results of experiments show the reconfigurable computing technology based on RMP is an ideal accelerating means to deal with the high-speed image processing tasks. High real time performance is obtained in our two applications on RMP.
基金National Natural Science Foundation of China(No.61301276)Xi’an Polytechnic University Young Scholar Backbone Supporting Plan,ChinaDiscipline Construction Funds of Xi’an Polytechnic University,China(No.107090811)
文摘A new algorithm is proposed to determine the actual length and the number of the protruding fibres of yarn based on a combination of image acquisition technology. First, a yarn hairiness image is obtained by the series of image processing procedures that include grayscale transformation,skew correction,yarn binary image acquisition and yarn core binary image obtaining. Then,the hairiness is realized in single pixel width by the usage of thinning algorithm. Finally, a baseline of yarn core margin is obtained,and pixels that match 8-neighbor template correctly are found by row scanning in a certain area. From this,these pixels are judged and the real crossover points of yarn core margin and hairiness,i. e.,the starting points of hairiness,are gained. The real length of the protruding fibres is calculated by tracking hairiness from the starting point constantly.
文摘The following article has been retracted due to special reason of the authors. This paper published in Vol.5 No. 2, 2014, has been removed from this site. Title: Template Matching from 2-D into 1-D Author: Yasser
文摘Template matching is a fundamental problem in pattern recognition, which has wide applications, especially in industrial inspection. In this paper, we propose a 1-D template matching algorithm which is an alternative for 2-D full search block matching algorithms. Our approach consists of three steps. In the first step the images are converted from 2-D into 1-D by summing up the intensity values of the image in two directions horizontal and vertical. In the second step, the template matching is performed among 1-D vectors using the similarity function sum of square difference. Finally, the decision will be taken based on the value of similarity function. Transformation template image and sub-images in the source image from 2-D grey level information into 1-D information vector reduce the dimensionality of the data and accelerate the computations. Experimental results show that the computational time of the proposed approach is faster and performance is better than three basic template matching methods. Moreover, our approach is robust to detect the target object with changes of illumination in the template also when the Gaussian noise added to the source image.
文摘为了提高小目标识别和分类的实时性,同时降低识别系统的资源消耗,本文提出了一种简易、高效的现场可编程门阵列(Field Programmable Gate Array,FPGA)小目标识别分类系统。该系统首先通过图像预处理消除图像噪点,并采用并行计算提升系统实时性。然后将处理后的图像与模板进行匹配计算得到识别结果,设计的模板匹配电路具有较小的硬件复杂度和较快的处理速度。实验结果表明,本文所提出的识别系统在680×480图像分辨下,可达137.5帧/s的处理速度,实时性强,同时仅消耗了9个块随机存储器(Block Random Access Memory,BRAM)和2个数字信号处理器(Digital Signal Processor,DSP),硬件资源消耗较少,在处理小目标识别和分类问题上有较好的实用价值。
文摘针对库水位传统量测方法中水尺易锈蚀倾斜,精度低且成本高的问题,该文提出一种不依赖水尺,基于图像匹配的库水位变动识别方法。首先对监控相机拍摄的库坝上游面光学图像进行畸变消除和透视变换,消除相机误差。进一步选取包含水面的感兴趣区域(region of interest,ROI)图像进行自适应二值化分割、形态学处理等前处理操作,将水面和库坝特征分离,突出水位线位置。最后,利用归一化互相关匹配算法(normalised cross correlation,NCC)对水位变动前后的两幅图像进行匹配计算,识别水位线变动距离。通过室内试验与现场测试验证上述方法实用性。结果表明:基于图像匹配的库水位动态识别方法可准确识别水位变动,相对误差约为5%,此算法鲁棒性较高。该研究可为库水位自动化、低成本监测提供一种新思路。
文摘家用厨锅在制造时安装手柄需要焊接螺母座,针对螺母座焊接位置不准确的问题,设计了厨锅锅底标签角度测量系统。该测量系统通过搭建视觉采集平台采集图像,利用模板匹配原理对锅底图像进行角度检测。通过对不同种类锅底图像进行滤波、阈值化与频域变换等图像处理算法制定感兴趣区域(ROI),由ROI依次创建形状模板;将采集到的图像经过预处理后根据已建好的同类模板进行匹配,匹配结果由Visual Studio 2019平台所建立的人机界面显示。实验表明,该测量系统平均误差可达0.08°,检出率达94%,平均检测时间0.35 s,明显优于传统的人工检测,能够满足工业的实际检测需求。
基金supported by National Natural Science Foundation of China (No.60672039)
文摘Template matching methods have been widely utilized to detect fabric defects in textile quality control. In this paper, a novel approach is proposed to design a flexible classifier for distinguishing flaws from twill fabrics by statistically learning from the normal fabric texture. Statistical information of natural and normal texture of the fabric can be extracted via collecting and analyzing the gray image. On the basis of this, both judging threshold and template are acquired and updated adaptively in real-time according to the real textures of fabric, which promises more flexibility and universality. The algorithms are experimented with images of fault free and faulty textile samples.
