Enormousmethods have been proposed for the detection and segmentation of blur and non-blur regions of the images.Due to the limited available information about blur type,scenario and the level of blurriness,detection ...Enormousmethods have been proposed for the detection and segmentation of blur and non-blur regions of the images.Due to the limited available information about blur type,scenario and the level of blurriness,detection and segmentation is a challenging task.Hence,the performance of the blur measure operator is an essential factor and needs improvement to attain perfection.In this paper,we propose an effective blur measure based on local binary pattern(LBP)with adaptive threshold for blur detection.The sharpness metric developed based on LBP used a fixed threshold irrespective of the type and level of blur,that may not be suitable for images with variations in imaging conditions,blur amount and type.Contrarily,the proposed measure uses an adaptive threshold for each input image based on the image and blur properties to generate improved sharpness metric.The adaptive threshold is computed based on the model learned through support vector machine(SVM).The performance of the proposed method is evaluated using two different datasets and is compared with five state-of-the-art methods.Comparative analysis reveals that the proposed method performs significantly better qualitatively and quantitatively against all of the compared methods.展开更多
In this study,an image binarization optimization algorithm,based on local threshold algorithms,is proposed because global and traditional local threshold segmentation algorithms cannot effectively address the problems...In this study,an image binarization optimization algorithm,based on local threshold algorithms,is proposed because global and traditional local threshold segmentation algorithms cannot effectively address the problems of nonuniform backgrounds of wood defect images.The proposed algorithm calculates the threshold by the mean,standard deviation and the extreme value of the window.The results indicate that this modified algorithm enhances the image segmentation for wood defect images on a complex background,which is much superior to the global threshold algorithm and the Bernsen algorithm,and slightly better than the Niblack algorithm and Sauvola algorithm.Compared with similar models,the algorithm proposed in this paper has higher segmentation accuracy,as high as 92.6%for wood defect images with a complex background.展开更多
目的:针对平板茧检测自动化程度低,识别效率不高等问题,提出一种基于局部阈值分割的平板茧表面印痕提取算法。方法:首先采用Canny算子提取图像边缘后进行膨胀处理获取平板茧表面印痕感兴趣区域(region of interest,ROI)。其次将ROI作为...目的:针对平板茧检测自动化程度低,识别效率不高等问题,提出一种基于局部阈值分割的平板茧表面印痕提取算法。方法:首先采用Canny算子提取图像边缘后进行膨胀处理获取平板茧表面印痕感兴趣区域(region of interest,ROI)。其次将ROI作为掩码统计平板茧原图对应区域的像素值均值,利用该均值与波动幅值设置局部分割阈值寻找平板茧印痕区域边缘。最后通过形态学处理与轮廓填充得到蚕茧表面完整印痕图像。结果:算法在主观表现评估与客观评价指标方面均有较好的提取效果,平均交并比mIOU与Dice系数分别达到86.42%、92.08%。结论:算法对平板茧的高精度辨别具有重要意义。展开更多
Based on photogrammetry technology,a novel localization method of micro-polishing robot,which is restricted within certain working space,is presented in this paper.On the basis of pinhole camera model,a new mathematic...Based on photogrammetry technology,a novel localization method of micro-polishing robot,which is restricted within certain working space,is presented in this paper.On the basis of pinhole camera model,a new mathematical model of vision localization of automated polishing robot is established.The vision localization is based on the distance-constraints of feature points.The method to solve the mathematical model is discussed.According to the characteristics of gray image,an adaptive method of automatic threshold selection based on connected components is presented.The center coordinate of the feature image point is resolved by bilinear interpolation gray square weighted algorithm.Finally,the mathematical model of testing system is verified by global localization test.The experimental results show that the vision localization system in working space has high precision.展开更多
The extraction of water bodies is essential for monitoring water resources,ecosystem services and the hydrological cycle,so analyzing water bodies from remote sensing images is necessary.The water index is designed to...The extraction of water bodies is essential for monitoring water resources,ecosystem services and the hydrological cycle,so analyzing water bodies from remote sensing images is necessary.The water index is designed to highlight water bodies in remote sensing images.We employ a new water index and digital image processing technology to extract water bodies automatically and accurately from Landsat 8 OLI images.Firstly,we preprocess Landsat 8 OLI images with radiometric calibration and atmospheric correction.Subsequently,we apply KT transformation,LBV transformation,AWEI nsh,and HIS transformation to the preprocessed image to calculate a new water index.Then,we perform linear feature enhancement and improve the local adaptive threshold segmentation method to extract small water bodies accurately.Meanwhile,we employ morphological enhancement and improve the local adaptive threshold segmentation method to extract large water bodies.Finally,we combine small and large water bodies to get complete water bodies.Compared with other traditional methods,our method has apparent advantages in water extraction,particularly in the extraction of small water bodies.展开更多
基金This work is supported by the BK-21 FOUR program and by the Creative Challenge Research Program(2021R1I1A1A01052521)through National Research Foundation of Korea(NRF)under Ministry of Education,Korea.
文摘Enormousmethods have been proposed for the detection and segmentation of blur and non-blur regions of the images.Due to the limited available information about blur type,scenario and the level of blurriness,detection and segmentation is a challenging task.Hence,the performance of the blur measure operator is an essential factor and needs improvement to attain perfection.In this paper,we propose an effective blur measure based on local binary pattern(LBP)with adaptive threshold for blur detection.The sharpness metric developed based on LBP used a fixed threshold irrespective of the type and level of blur,that may not be suitable for images with variations in imaging conditions,blur amount and type.Contrarily,the proposed measure uses an adaptive threshold for each input image based on the image and blur properties to generate improved sharpness metric.The adaptive threshold is computed based on the model learned through support vector machine(SVM).The performance of the proposed method is evaluated using two different datasets and is compared with five state-of-the-art methods.Comparative analysis reveals that the proposed method performs significantly better qualitatively and quantitatively against all of the compared methods.
基金supported by National Forestry Public Welfare Industry Scientific Research Special Subsidy Project(201304502)
文摘In this study,an image binarization optimization algorithm,based on local threshold algorithms,is proposed because global and traditional local threshold segmentation algorithms cannot effectively address the problems of nonuniform backgrounds of wood defect images.The proposed algorithm calculates the threshold by the mean,standard deviation and the extreme value of the window.The results indicate that this modified algorithm enhances the image segmentation for wood defect images on a complex background,which is much superior to the global threshold algorithm and the Bernsen algorithm,and slightly better than the Niblack algorithm and Sauvola algorithm.Compared with similar models,the algorithm proposed in this paper has higher segmentation accuracy,as high as 92.6%for wood defect images with a complex background.
文摘目的:针对平板茧检测自动化程度低,识别效率不高等问题,提出一种基于局部阈值分割的平板茧表面印痕提取算法。方法:首先采用Canny算子提取图像边缘后进行膨胀处理获取平板茧表面印痕感兴趣区域(region of interest,ROI)。其次将ROI作为掩码统计平板茧原图对应区域的像素值均值,利用该均值与波动幅值设置局部分割阈值寻找平板茧印痕区域边缘。最后通过形态学处理与轮廓填充得到蚕茧表面完整印痕图像。结果:算法在主观表现评估与客观评价指标方面均有较好的提取效果,平均交并比mIOU与Dice系数分别达到86.42%、92.08%。结论:算法对平板茧的高精度辨别具有重要意义。
基金supported by the National High Technology Research and Development Program of China (Grant No. 2006AA04Z214)the National Natural Science Foundation of China (Grant No. 50575092)
文摘Based on photogrammetry technology,a novel localization method of micro-polishing robot,which is restricted within certain working space,is presented in this paper.On the basis of pinhole camera model,a new mathematical model of vision localization of automated polishing robot is established.The vision localization is based on the distance-constraints of feature points.The method to solve the mathematical model is discussed.According to the characteristics of gray image,an adaptive method of automatic threshold selection based on connected components is presented.The center coordinate of the feature image point is resolved by bilinear interpolation gray square weighted algorithm.Finally,the mathematical model of testing system is verified by global localization test.The experimental results show that the vision localization system in working space has high precision.
基金Auhui Provincial Key Research and Development Project(No.202004a07020050)National Natural Science Foundation of China Youth Program(No.61901006)。
文摘The extraction of water bodies is essential for monitoring water resources,ecosystem services and the hydrological cycle,so analyzing water bodies from remote sensing images is necessary.The water index is designed to highlight water bodies in remote sensing images.We employ a new water index and digital image processing technology to extract water bodies automatically and accurately from Landsat 8 OLI images.Firstly,we preprocess Landsat 8 OLI images with radiometric calibration and atmospheric correction.Subsequently,we apply KT transformation,LBV transformation,AWEI nsh,and HIS transformation to the preprocessed image to calculate a new water index.Then,we perform linear feature enhancement and improve the local adaptive threshold segmentation method to extract small water bodies accurately.Meanwhile,we employ morphological enhancement and improve the local adaptive threshold segmentation method to extract large water bodies.Finally,we combine small and large water bodies to get complete water bodies.Compared with other traditional methods,our method has apparent advantages in water extraction,particularly in the extraction of small water bodies.
