2010 6th Iranian Conference on Machine Vision and Image Processing最新文献_第3页

A simple method for calculating vehicle density in traffic images 一种计算交通图像中车辆密度的简单方法

2010 6th Iranian Conference on Machine Vision and Image Processing Pub Date : 2010-10-01 DOI: 10.1109/IRANIANMVIP.2010.5941176

Tahere Royani, J. Haddadnia, M. Pooshideh

{"title":"A simple method for calculating vehicle density in traffic images","authors":"Tahere Royani, J. Haddadnia, M. Pooshideh","doi":"10.1109/IRANIANMVIP.2010.5941176","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2010.5941176","url":null,"abstract":"Calculating of vehicles density in traffic images is a challenging research topic as it has to directly deal with hostile but realistic conditions on the road, such as uncontrolled illuminations, cast shadows, and visual occlusion. Yet, the outcome of being able to accurately count and resolve vehicles under such conditions has tremendous benefit to traffic surveillance. Accurate vehicle count enables the extraction of important traffic information such as congestion level and lane occupancy. There are different methods for vehicles counting from traffic images that emphasize on the accuracy, but most of them suffer from long time process and computational complexity, so they can't be used in real-time condition. This paper proposed a novel simple method for traffic density calculation in multiple vehicle occlusions based on counting object pixels and assigning a distance index to each region of image that concentrates on time and computational complexity and has tolerable accuracy in traffic density calculation. Suppose that the occluded vehicles are segmented from the road background by previously proposed vehicle segmentation method. The proposed method has been tested on real-world monocular traffic images with multiple vehicle occlusions. The experimental results show that the proposed method can provide real-time and useful information for traffic surveillance.","PeriodicalId":350778,"journal":{"name":"2010 6th Iranian Conference on Machine Vision and Image Processing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127719405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Full automatic micro calcification detection in mammogram images using artificial neural network and Gabor wavelets 基于人工神经网络和Gabor小波的乳房x线图像全自动微钙化检测

2010 6th Iranian Conference on Machine Vision and Image Processing Pub Date : 2010-10-01 DOI: 10.1109/IRANIANMVIP.2010.5941183

AmirEhsan Lashkari

引用次数: 14

Real-time fusion of multi-focus images for visual sensor networks 面向视觉传感器网络的多焦点图像实时融合

2010 6th Iranian Conference on Machine Vision and Image Processing Pub Date : 2010-10-01 DOI: 10.1109/IRANIANMVIP.2010.5941140

Mohammad Haghighat, A. Aghagolzadeh, Hadi Seyedarabi

引用次数: 69

A novel image encryption algorithm based on hash function 一种基于哈希函数的图像加密算法

2010 6th Iranian Conference on Machine Vision and Image Processing Pub Date : 2010-10-01 DOI: 10.1109/IRANIANMVIP.2010.5941167

Seyed Mohammad Seyedzade, S. Mirzakuchaki, Reza Ebrahimi Atani

引用次数: 62

Eroded money notes recognition using wavelet transform 基于小波变换的侵蚀纸币识别

2010 6th Iranian Conference on Machine Vision and Image Processing Pub Date : 2010-10-01 DOI: 10.1109/IRANIANMVIP.2010.5941144

F. Daraee, S. Mozaffari

引用次数: 13

Assessment and elimination of errors due to electrode displacements in elliptical and square models in EIT EIT中椭圆和方形模型中电极位移误差的评估与消除

2010 6th Iranian Conference on Machine Vision and Image Processing Pub Date : 2010-10-01 DOI: 10.1109/IRANIANMVIP.2010.5941160

A. Javaherian, A. Movafeghi, R. Faghihi

{"title":"Assessment and elimination of errors due to electrode displacements in elliptical and square models in EIT","authors":"A. Javaherian, A. Movafeghi, R. Faghihi","doi":"10.1109/IRANIANMVIP.2010.5941160","DOIUrl":"https://doi.org/10.1109/IRANIANMVIP.2010.5941160","url":null,"abstract":"This study modifies a Tikhonov regularized \"maximum a posteriori\" algorithm proposed for reconstructing both the conductivity changes and electrode positioning variations in EIT and uses this algorithm for reconstructing images of 2d elliptical and square models, instead of simple circular model used in previous works. This algorithm had been proposed By C. Gomez for compensating the errors due to electrode movements in image reconstruction. The jacobian matrix has been constructed via perturbation both conductivity and electrode positioning. The prior image matrix should incorporate some kind of augmented inter-electrode positioning correlations to impose a smoothness constraint on both the conductivity change distribution and electrode movement. For each model, conductivity change image is reconstructed in 3 cases: a) With no electrode displacement using standard algorithm b) With electrode displacement using standard algorithm c) With electrode displacement using proposed algorithm. In all models, a comparison between 3 cases has been implemented. Also, the results obtained from each model have been compared with the other models in similar cases. The results obtained in this study will be useful to investigate the ellipticity effects of organs being imaged in clinical applications. Moreover, the effects of model deviation from circular form on reconstructed images can be used in special industrial applications.","PeriodicalId":350778,"journal":{"name":"2010 6th Iranian Conference on Machine Vision and Image Processing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131067307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Temporal Conditional Random Fields: A conditional state space predictor for visual tracking 时间条件随机场:用于视觉跟踪的条件状态空间预测器

2010 6th Iranian Conference on Machine Vision and Image Processing Pub Date : 2010-10-01 DOI: 10.1109/IRANIANMVIP.2010.5941137

M. Shafiee, Z. Azimifar, P. Fieguth

引用次数: 1

Automatic extraction of positive cells in pathology images of meningioma based on the maximal entropy principle and HSV color space 基于最大熵原理和HSV色彩空间的脑膜瘤病理图像阳性细胞自动提取

2010 6th Iranian Conference on Machine Vision and Image Processing Pub Date : 2010-10-01 DOI: 10.1109/IRANIANMVIP.2010.5941150

V. Anari, P. Mahzouni, R. Amirfattahi

引用次数: 4

Human action recognition by RANSAC based salient features of skeleton history image using ANFIS 基于RANSAC的骨骼历史图像显著特征的ANFIS人体动作识别

2010 6th Iranian Conference on Machine Vision and Image Processing Pub Date : 2010-10-01 DOI: 10.1109/IRANIANMVIP.2010.6313969

Maryam Ziaeefard, Hossein Ebrahimnezhad

引用次数: 3

Two-dimensional variable step-size normalized least mean squares and affine projection adaptive filter algorithms 二维变步长归一化最小均方和仿射投影自适应滤波算法

2010 6th Iranian Conference on Machine Vision and Image Processing Pub Date : 2010-10-01 DOI: 10.1109/IRANIANMVIP.2010.5941182

M. Abadi, S. Nikbakht

引用次数: 1