共查询到19条相似文献,搜索用时 62 毫秒
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对基于机器视觉的黑色O形橡胶圈缺陷检测系统展开了研究,对采集到的橡胶圈图像进行相关处理以便检测出缺陷特征,通过改进后的中值滤波滤除噪声,建立图像直方图了解缺陷特征的灰度分布情况,比较了几种边缘检测算子的检测效果,并通过实验仿真验证了算法的可行性。 相似文献
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提出并设计了一种基于机器视觉的注塑件焦料杂质缺陷检测系统,通过对多光源非线性自动调光算法的研究,提高了复杂生产环境下注塑件图像采集质量,并经高斯滤波、灰度图像、自适应阈值处理、Canny边缘检测等图像处理技术,可实现注塑件不同检测精度下缺陷检测。经现场测试证明,在1 mm以上缺陷检测精度下,杂质缺陷的召回率为0.918,误检率为0.046,识别速度为每秒30帧,图像处理算法性能稳定,解决了复杂注塑件生产环境下检测精度低、检测效率低的问题。 相似文献
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针对目前磁控溅射薄膜件人工检测效率低的问题,结合企业需求,设计了一种基于机器视觉技术的磁控溅射薄膜件划痕自动检测系统,实现对产品表面各种划痕的自动检测。首先对采集到的图像进行校正,利用标准图像创建模板,通过形状模板匹配提取样本图像中感兴趣的区域。然后将图像分解成低频和高频两部分,对低频部分进行先膨胀后腐蚀的操作,对高频部分进行中值滤波以去除噪声,图像合成后通过取反和灰度缩放生成增强图像;最后采用二维Otsu拟合线阈值分割法对图像进行分割,采用选取指定形状特征和骨架提取法对划痕缺陷进行提取和测量。对100件样品进行多次随机验证的结果表明,本文设计的系统能快速、准确、高效地提取并测量划痕缺陷,每个样品检测的平均耗时仅0.25 s,正检率达98.5%。该方案与人工检测比,速度更快、准确度更高,可以满足工业应用的需求。 相似文献
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将机器视觉引入电镀件表面缺陷检测中,设计了一种基于机器视觉的电镀件表面缺陷检测系统。该系统由工控机、图像采集卡、工业相机、伺服电机、照明装置和运动控制卡组成。获取电镀件表面光学图像并经预处理后,利用算法提取出图像中缺陷区域边界特征,通过计算用于标记缺陷区域边界特征的白色像素点个数,并与设定的阈值做比较,实现电镀件表面缺陷检测。该系统满足电镀件表面缺陷在线检测的要求。 相似文献
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机器视觉技术在玻璃基板缺陷检测设备中的应用 总被引:1,自引:0,他引:1
简单介绍了机器视觉的基本概念及相关组成,分析了以机器视觉为理论基础的光学检测设备在玻璃基板缺陷检测中的应用。通过对玻璃基板常见缺陷的介绍,指出了相关检测设备在具体的缺陷检测中需要注意的事项。 相似文献
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刘克颜 《煤炭加工与综合利用》2021,(2):21-22
针对选煤厂胶带运输机和刮板运输机溜槽堵塞检测准确性差的现状,提出了一种基于机器视觉的检测方案.方案采取物料覆盖面积测定+特征量比较的综合判定方法,能在堵塞发生的初期准确预告故障,并以视频联动的方式及时通知集控操作人员. 相似文献
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设计了一种基于机器视觉的涂装缺陷检测系统来检测汽车零件表面的孔洞边缘缺陷,并在Halcon软件中实现了相关检测算法.首先搭建了检测平台获取图像信息,运用迭代加权拟合的方法实现了对孔洞感兴趣区域(ROI)的定位与提取,从而缩短检测时间;再使用一种带阻滤波器对图像进行预处理,减少了表面反光;最后运用阈值分割等方法对涂装缺陷特征进行识别和提取.该法能快速、准确地识别提取涂装缺陷特征,平均单次识别时间为320 ms,识别准确率为97%,满足工业涂装缺陷检测的要求. 相似文献
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针对在薄膜加工中恒温箱内温度过高或过低导致薄膜破裂,但人工因恒温箱的高温和结构遮挡难以及时发现薄膜破裂这一问题,结合目前机器视觉的方法,提出一种薄膜破裂图像检测技术,能够监测薄膜的破裂情况,降低生产损耗。在对横拉薄膜破裂区域进行图像处理方法的研究当中,对常见图像的增强、去噪、边缘分割技术分别进行了分析和比较,找出了适用于横拉薄膜破裂图像的预处理、分割方法。通过对薄膜破裂图像的分析与比较中,依据破裂形式将破裂方式分为小范围破裂和纵向破裂两种,并找到了面积、周长区分两种破裂方式的视觉识别特征参数,为调整加工温度参数起到了积极意义。结果表明,所提出的检测技术能够准确判断薄膜破裂形式,准确率为92.7 %,可满足工业生产需求。 相似文献
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针对煤泥浮选泡沫图像中存在的噪声干扰和气泡粘连等问题,提出了一种基于机器视觉的分割模型,采用煤泥浮选泡沫图像分割算法对实验室采集到的煤泥浮选泡沫图像进行图像分割试验。结果表明,基于机器视觉的煤泥浮选泡沫图像分割模型主要包括ROF模型去除图像噪声和基于顶帽、底帽变换的粘连泡沫分割。ROF模型基于有界全变分函数空间,该空间中函数的不连续正好与图像中物体的边缘轮廓对应,非常适于泡沫图像去噪处理;顶帽变换使得泡沫与泡沫之间的间隙变大,解决了气泡粘连问题;最后采用分水岭算法完成对泡沫的分割。理论分析及实验室研究均表明,该方法可准确、快速地分割出复杂煤泥浮选泡沫图像中的泡沫,分割准确率高达81.1%,验证了分割方法的有效性。 相似文献
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《Ceramics International》2022,48(8):11085-11093
Ceramic tiles are widely used in the construction field. In actual production, the difficulty in extracting texture ceramic tile features and the small size of defects lead to low detection accuracy and inefficiency. To solve these problems, we propose a detection method based on improved YOLOv5s. Firstly, the network layer is deepened in the backbone network and the attention mechanism CBAM module is added. Then, a small-scale detection layer is added, and the model is increased from a three-output prediction layer to a four-output prediction layer. Thirdly, the network feature fusion is enhanced in the neck network. Finally, the original convolution is replaced with depthwise separable convolution, and a lightweight ceramic tile detection system is constructed. Experimental results show that our model can solve the problems caused by small defects and insufficient feature information effectively. 相似文献
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Tuija Jetsu Ville Heikkinen Anahit Pogosova Timo Jaaskelainen Jussi Parkkinen 《Color research and application》2009,34(5):341-350
Recent break‐throughs in retinal imaging have raised new questions for color vision research, and the existing color vision models should be re‐evaluated. Many color vision models are based on an assumption that there are no differences in the detection phase, neither in the spatial configuration nor in the spectral sensitivities of cells. In this article, we have run experiments with four different color vision models. This evaluation gives us more knowledge about the essential properties of the models. We show how the tested color vision models are able to replicate the behaviour of human color vision by evaluating their performance in Farnsworth‐Munsell 100‐Hue color vision test. Also, the wavelength discrimination power of each model is presented and the properties of color spaces spanned by models are examined using samples from Munsell Book of Color. Our experiments show that there are large differences in the properties of different models. © 2009 Wiley Periodicals, Inc. Col Res Appl, 34, 341–350, 2009 相似文献
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Saeedeh Abasi Mohammad A. Tehran Mark D. Fairchild 《Color research and application》2020,45(4):632-643
Image edge detection based on low-level feature is usually performed on gray-scale images. Some methods have been developed for edge detection on colour images based on low-level feature, but they are not consistent with human colour perception. This research provides a new algorithm for edge detection based on the “HyAB” large-colour-difference formula. This algorithm uses Sobel operators for gradient-magnitude calculations and Canny methods for localizing edge points. The performance of the new algorithm is qualitatively compared with Sobal and Canny methods using some challenging colour images. The results indicate that gradient magnitudes are best calculated using the HyAB colour-difference formula, and that CIELAB and CIEDE2000 differences are not suitable for this purpose. Definition of gradient magnitudes according human perception is essential in applications such as quality control of fabric printing, calculation of disruptive colouration, and so on. The new algorithm is successful in accuracy and fine edge detection in comparison with the Sobel and Canny methods. The new method is quantitatively compared with state-of-the-art methods using three datasets including BSDS500, MBDD, and BIPED. The correctness and accuracy of annotations of images in datasets have an important effect on results. The new method does not reach scores better than deep-learning-based methods, but it is simple and does not need training. It could probably have better results with improving noise-suppression. 相似文献