提出了一种利用"bag of words"模型对视频内容进行建模和匹配的方法。通过量化视频帧的局部特征构建视觉关键词(visual words)辞典,将视频的子镜头表示成若干视觉关键词的集合。在此基础上构建基于子镜头的视觉关键词词组的...提出了一种利用"bag of words"模型对视频内容进行建模和匹配的方法。通过量化视频帧的局部特征构建视觉关键词(visual words)辞典,将视频的子镜头表示成若干视觉关键词的集合。在此基础上构建基于子镜头的视觉关键词词组的倒排索引,用于视频片段的匹配和检索。这种方法保留了局部特征的显著性及其相对位置关系,而且有效地压缩了视频的表达,加速的视频的匹配和检索过程。实验结果表明,和已有方法相比,基于"bag of words"的视频匹配方法在大视频样本库上获得了更高的检索精度和检索速度。展开更多
The current detection technology for vegetable pests mainly relies on artificial statistics,which exists many shortages such as requiring a large amount of labor,low efficiency,feedback delay and artificial faults.By ...The current detection technology for vegetable pests mainly relies on artificial statistics,which exists many shortages such as requiring a large amount of labor,low efficiency,feedback delay and artificial faults.By rapid detection and image processing technology targeting at vegetable pests,not only can reduce manpower and pesticide use,but also provide decision support for precise spraying and improve the quality of vegetables.Practical research achievements are still relatively lacking on the rapid identification technology based on image processing technology in vegetable pests.Given the above background,this paper presents a classification and recognition scheme based on the bag-of-words model and support vector machine(BOF-SVM)on four important southern vegetable pests including Whiteflies,Phyllotreta Striolata,Plutella Xylostella and Thrips.This paper consists of four sub-algorithms.The first sub-algorithm is to compute the character description of pest images based on scale-invariant feature transformation.The second sub-algorithm is to compute the visual vocabulary based on bag of features.The third sub-algorithm is to compute the classifier of pests based on support vector machines.The last one is to classify the pest images using the classifier.In this study,C++and Python language were used as implementation technologies with OpenCV and LibSVM function library based on BOF-SVM classification algorithm.Experiments showed that the average recognition accuracy was 91.56%for a single image category judgment with 80 images from the real environment,and the average time was 0.39 seconds.This algorithm has achieved the ideal operating speed and precision.It can provide decision support for UAV precise spraying,and also has good application prospect in agriculture.展开更多
将Bag of Features算法引入汽车图像识别领域中,并提出了将DoG(Difference of Gaussian)特征提取算法和PLSA分类算法结合在一起实现车辆和背景图像分类。首先用DoG特征提取算法提取图像特征,用这些特征聚类产生码书并对图像进行柱状图描...将Bag of Features算法引入汽车图像识别领域中,并提出了将DoG(Difference of Gaussian)特征提取算法和PLSA分类算法结合在一起实现车辆和背景图像分类。首先用DoG特征提取算法提取图像特征,用这些特征聚类产生码书并对图像进行柱状图描述,最后设计PLSA分类器对车辆图像和背景图像进行分类。实验对比了该算法与Tamura纹理特征算法和Gabor纹理特征算法在车辆图像识别中的效果。结果表明本文算法分类正确率优于另外两种方法。展开更多
This paper presents a novel framework for human action recognition based on salient object detection and a new combination of local and global descriptors. We first detect salient objects in video frames and only extr...This paper presents a novel framework for human action recognition based on salient object detection and a new combination of local and global descriptors. We first detect salient objects in video frames and only extract features for such objects.We then use a simple strategy to identify and process only those video frames that contain salient objects. Processing salient objects instead of all frames not only makes the algorithm more efficient, but more importantly also suppresses the interference of background pixels. We combine this approach with a new combination of local and global descriptors, namely3D-SIFT and histograms of oriented optical flow(HOOF), respectively. The resulting saliency guided3D-SIFT–HOOF(SGSH) feature is used along with a multi-class support vector machine(SVM) classifier for human action recognition. Experiments conducted on the standard KTH and UCF-Sports action benchmarks show that our new method outperforms the competing state-of-the-art spatiotemporal feature-based human action recognition methods.展开更多
The traditional information hiding methods embed the secret information by modifying the carrier,which will inevitably leave traces of modification on the carrier.In this way,it is hard to resist the detection of steg...The traditional information hiding methods embed the secret information by modifying the carrier,which will inevitably leave traces of modification on the carrier.In this way,it is hard to resist the detection of steganalysis algorithm.To address this problem,the concept of coverless information hiding was proposed.Coverless information hiding can effectively resist steganalysis algorithm,since it uses unmodified natural stego-carriers to represent and convey confidential information.However,the state-of-the-arts method has a low hidden capacity,which makes it less appealing.Because the pixel values of different regions of the molecular structure images of material(MSIM)are usually different,this paper proposes a novel coverless information hiding method based on MSIM,which utilizes the average value of sub-image’s pixels to represent the secret information,according to the mapping between pixel value intervals and secret information.In addition,we employ a pseudo-random label sequence that is used to determine the position of sub-images to improve the security of the method.And the histogram of the Bag of words model(BOW)is used to determine the number of subimages in the image that convey secret information.Moreover,to improve the retrieval efficiency,we built a multi-level inverted index structure.Furthermore,the proposed method can also be used for other natural images.Compared with the state-of-the-arts,experimental results and analysis manifest that our method has better performance in anti-steganalysis,security and capacity.展开更多
Entrained flow adsorption using activated carbon as the adsorbent is widely adopted for PCDDs/Fs-abatement in municipal solid waste incineration (MSWI) process. The effects of operating parameters including flue gas t...Entrained flow adsorption using activated carbon as the adsorbent is widely adopted for PCDDs/Fs-abatement in municipal solid waste incineration (MSWI) process. The effects of operating parameters including flue gas temperature, feeding rate of activated carbon, polychlorinated dibenzodioxins and polychlorinated dibenzofurans (PCDDs/Fs) concentration at the inlet of the air pollution control device (APCD), filter materials, pressure drop on PCDDs/Fs removal efficiency are reviewed and commented upon in this paper. Evaluation on the various mechanistic models for entrained flow adsorption is carried out based on the computational simulation in terms of the actual operating condition and theoretical analysis. Finally, an advancement of en- trained flow adsorption in combination of dual bag filter is introduced.展开更多
The combustion characteristics of blast furnace bag dust(BD) and three kinds of coal—Shenhua(SH) bituminous coal, Pingluo(PL) anthracite, and Yangquan(YQ) anthracite—were obtained via non-isothermal thermogravimetry...The combustion characteristics of blast furnace bag dust(BD) and three kinds of coal—Shenhua(SH) bituminous coal, Pingluo(PL) anthracite, and Yangquan(YQ) anthracite—were obtained via non-isothermal thermogravimetry. The combustion characteristics with different mixing ratios were also investigated. The physical and chemical properties of the four samples were investigated in depth using particle size analysis, Scanning electron microscopy, X-ray diffraction, X-ray fluorescence analysis, and Raman spectroscopy. The results show that the conversion rate of the three kinds of pulverized coals is far greater than that of the BD. The comprehensive combustion characteristics of the three types of pulverized coals rank in the order SH > PL > YQ. With the addition of BD, the characteristic parameters of the combustion reaction of the blend showed an increasing trend. The Coats–Redfern model used in this study fit well with the experimental results. As the BD addition increased from 5 wt% to 10 wt%, the activation energy of combustion reactions decreased from 68.50 to 66.74 k J/mol for SH, 118.34 to 110.75 kJ/mol for PL, and 146.80 to 122.80 kJ/mol for YQ. These results also provide theoretical support for the practical application of blast furnace dust for blast furnace injection.展开更多
文摘提出了一种利用"bag of words"模型对视频内容进行建模和匹配的方法。通过量化视频帧的局部特征构建视觉关键词(visual words)辞典,将视频的子镜头表示成若干视觉关键词的集合。在此基础上构建基于子镜头的视觉关键词词组的倒排索引,用于视频片段的匹配和检索。这种方法保留了局部特征的显著性及其相对位置关系,而且有效地压缩了视频的表达,加速的视频的匹配和检索过程。实验结果表明,和已有方法相比,基于"bag of words"的视频匹配方法在大视频样本库上获得了更高的检索精度和检索速度。
基金This work was supported by the National Spark Program(2015GA780002)Guangdong Province Science and Technology Program(2015A020224042).
文摘The current detection technology for vegetable pests mainly relies on artificial statistics,which exists many shortages such as requiring a large amount of labor,low efficiency,feedback delay and artificial faults.By rapid detection and image processing technology targeting at vegetable pests,not only can reduce manpower and pesticide use,but also provide decision support for precise spraying and improve the quality of vegetables.Practical research achievements are still relatively lacking on the rapid identification technology based on image processing technology in vegetable pests.Given the above background,this paper presents a classification and recognition scheme based on the bag-of-words model and support vector machine(BOF-SVM)on four important southern vegetable pests including Whiteflies,Phyllotreta Striolata,Plutella Xylostella and Thrips.This paper consists of four sub-algorithms.The first sub-algorithm is to compute the character description of pest images based on scale-invariant feature transformation.The second sub-algorithm is to compute the visual vocabulary based on bag of features.The third sub-algorithm is to compute the classifier of pests based on support vector machines.The last one is to classify the pest images using the classifier.In this study,C++and Python language were used as implementation technologies with OpenCV and LibSVM function library based on BOF-SVM classification algorithm.Experiments showed that the average recognition accuracy was 91.56%for a single image category judgment with 80 images from the real environment,and the average time was 0.39 seconds.This algorithm has achieved the ideal operating speed and precision.It can provide decision support for UAV precise spraying,and also has good application prospect in agriculture.
文摘将Bag of Features算法引入汽车图像识别领域中,并提出了将DoG(Difference of Gaussian)特征提取算法和PLSA分类算法结合在一起实现车辆和背景图像分类。首先用DoG特征提取算法提取图像特征,用这些特征聚类产生码书并对图像进行柱状图描述,最后设计PLSA分类器对车辆图像和背景图像进行分类。实验对比了该算法与Tamura纹理特征算法和Gabor纹理特征算法在车辆图像识别中的效果。结果表明本文算法分类正确率优于另外两种方法。
基金funded by Iraqi Ministry of Higher Education and Scientific Research (MHESR)
文摘This paper presents a novel framework for human action recognition based on salient object detection and a new combination of local and global descriptors. We first detect salient objects in video frames and only extract features for such objects.We then use a simple strategy to identify and process only those video frames that contain salient objects. Processing salient objects instead of all frames not only makes the algorithm more efficient, but more importantly also suppresses the interference of background pixels. We combine this approach with a new combination of local and global descriptors, namely3D-SIFT and histograms of oriented optical flow(HOOF), respectively. The resulting saliency guided3D-SIFT–HOOF(SGSH) feature is used along with a multi-class support vector machine(SVM) classifier for human action recognition. Experiments conducted on the standard KTH and UCF-Sports action benchmarks show that our new method outperforms the competing state-of-the-art spatiotemporal feature-based human action recognition methods.
基金This work is supported,in part,by the National Natural Science Foundation of China under grant numbers U1536206,U1405254,61772283,61602253,61672294,61502242in part,by the Jiangsu Basic Research Programs-Natural Science Foundation under grant numbers BK20150925 and BK20151530+1 种基金in part,by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fundin part,by the Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)fund,China.
文摘The traditional information hiding methods embed the secret information by modifying the carrier,which will inevitably leave traces of modification on the carrier.In this way,it is hard to resist the detection of steganalysis algorithm.To address this problem,the concept of coverless information hiding was proposed.Coverless information hiding can effectively resist steganalysis algorithm,since it uses unmodified natural stego-carriers to represent and convey confidential information.However,the state-of-the-arts method has a low hidden capacity,which makes it less appealing.Because the pixel values of different regions of the molecular structure images of material(MSIM)are usually different,this paper proposes a novel coverless information hiding method based on MSIM,which utilizes the average value of sub-image’s pixels to represent the secret information,according to the mapping between pixel value intervals and secret information.In addition,we employ a pseudo-random label sequence that is used to determine the position of sub-images to improve the security of the method.And the histogram of the Bag of words model(BOW)is used to determine the number of subimages in the image that convey secret information.Moreover,to improve the retrieval efficiency,we built a multi-level inverted index structure.Furthermore,the proposed method can also be used for other natural images.Compared with the state-of-the-arts,experimental results and analysis manifest that our method has better performance in anti-steganalysis,security and capacity.
基金Project supported by the National Basic Research Program (973) of China (No. G1999022211) and the National Natural Science Founda-tion of China (No. N59836210)
文摘Entrained flow adsorption using activated carbon as the adsorbent is widely adopted for PCDDs/Fs-abatement in municipal solid waste incineration (MSWI) process. The effects of operating parameters including flue gas temperature, feeding rate of activated carbon, polychlorinated dibenzodioxins and polychlorinated dibenzofurans (PCDDs/Fs) concentration at the inlet of the air pollution control device (APCD), filter materials, pressure drop on PCDDs/Fs removal efficiency are reviewed and commented upon in this paper. Evaluation on the various mechanistic models for entrained flow adsorption is carried out based on the computational simulation in terms of the actual operating condition and theoretical analysis. Finally, an advancement of en- trained flow adsorption in combination of dual bag filter is introduced.
基金supported by the Natural Science Foundation for Young Scientists of China (No. 51804026)the Young Elite Scientists Sponsorship Program by China Association for Science and Technology (No. 2017QNRC001)the National Natural Science Foundation of China (No. 51774032)
文摘The combustion characteristics of blast furnace bag dust(BD) and three kinds of coal—Shenhua(SH) bituminous coal, Pingluo(PL) anthracite, and Yangquan(YQ) anthracite—were obtained via non-isothermal thermogravimetry. The combustion characteristics with different mixing ratios were also investigated. The physical and chemical properties of the four samples were investigated in depth using particle size analysis, Scanning electron microscopy, X-ray diffraction, X-ray fluorescence analysis, and Raman spectroscopy. The results show that the conversion rate of the three kinds of pulverized coals is far greater than that of the BD. The comprehensive combustion characteristics of the three types of pulverized coals rank in the order SH > PL > YQ. With the addition of BD, the characteristic parameters of the combustion reaction of the blend showed an increasing trend. The Coats–Redfern model used in this study fit well with the experimental results. As the BD addition increased from 5 wt% to 10 wt%, the activation energy of combustion reactions decreased from 68.50 to 66.74 k J/mol for SH, 118.34 to 110.75 kJ/mol for PL, and 146.80 to 122.80 kJ/mol for YQ. These results also provide theoretical support for the practical application of blast furnace dust for blast furnace injection.
