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2011 Sixth International Conference on Image and Graphics最新文献

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A Classification Algorithm to Distinguish Image as Haze or Non-haze 一种区分图像雾霾与非雾霾的分类算法
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.22
Xiaoliang Yu, Chuangbai Xiao, M. Deng, Li Peng
{"title":"A Classification Algorithm to Distinguish Image as Haze or Non-haze","authors":"Xiaoliang Yu, Chuangbai Xiao, M. Deng, Li Peng","doi":"10.1109/ICIG.2011.22","DOIUrl":"https://doi.org/10.1109/ICIG.2011.22","url":null,"abstract":"The technology of image dehazing can only work for haze images, but in batch and real-time processing, only relying on human visual system judge whether the image is haze or non-haze image, is unrealistic, so how to determine whether there are haze or non-haze images is needed to be solved. In this paper, we proposed a method to judge whether a given image is haze. According to the difference between the haze and non-haze images, we extract three eigen values, including image visibility, intensity of dark channel and image contrast, then combine with support vector machine to make judgment of image state which is haze or non-haze, obtaining high recognition rate. Experimental results show that our method is feasible and effective. Our method for bath and real-time processing provide the basis for judging image state, promoting the wide application of image dehazing.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128407682","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: 32
Dynamic Background Subtraction Using Spatial-Color Binary Patterns 使用空间颜色二元模式的动态背景减法
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.76
Wei Zhou, Yu Liu, Weiming Zhang, Liansheng Zhuang, Nenghai Yu
{"title":"Dynamic Background Subtraction Using Spatial-Color Binary Patterns","authors":"Wei Zhou, Yu Liu, Weiming Zhang, Liansheng Zhuang, Nenghai Yu","doi":"10.1109/ICIG.2011.76","DOIUrl":"https://doi.org/10.1109/ICIG.2011.76","url":null,"abstract":"In this paper, an efficient approach for background modeling and subtraction is proposed. It's based on a novel spatial-color feature extraction operator named spatial-color binary patterns(SCBP). As the name implies, features extracted by this operator include spatial texture and color information. In addition, a refine module is designed to refine the contour of moving objects. Using the proposed method, we improve the accuracy of subtracting the background and detecting moving objects in dynamic scenes. A data-driven model is used in our method. For each pixel, first, a histogram of SCBP is extracted from the circular egion, and then a model consist of several histograms is built. For a new observed frame, each pixel is labeled either background or foreground according to the matching degree between its SCBP histogram and its model, then the label is refined and finally the model of this pixel is updated. The proposed pproach is tested on challenging video sequences, which shows that the proposed method performs much better than several texture-based methods.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129897648","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: 16
Brain MR Image Tumor Segmentation with Ventricular Deformation 基于脑室变形的脑MR图像肿瘤分割
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.141
Kai Xiao, A. Hassanien, Y. Sun, E. Ng
{"title":"Brain MR Image Tumor Segmentation with Ventricular Deformation","authors":"Kai Xiao, A. Hassanien, Y. Sun, E. Ng","doi":"10.1109/ICIG.2011.141","DOIUrl":"https://doi.org/10.1109/ICIG.2011.141","url":null,"abstract":"This paper addresses the issue of the weak association between brain MRI intensity value and anatomical meaning of MR image pixels. By investigating the deformation on brain lateral ventricles and compression from tumor, the correlation between them is quantified and utilized. With the proposed feature extraction component, lateral ventricular deformation is transformed into an additional feature for brain tumor segmentation. Some comparative experiments using both supervised and unsupervised pattern recognition segmentation methods show the improved tumor segmentation accuracy in some image cases.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126838954","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: 3
Hierarchical Joint Bilateral Filtering for Depth Post-Processing 深度后处理的层次联合双边滤波
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.24
Qingqing Yang, Lianghao Wang, Dongxiao Li, Ming Zhang
{"title":"Hierarchical Joint Bilateral Filtering for Depth Post-Processing","authors":"Qingqing Yang, Lianghao Wang, Dongxiao Li, Ming Zhang","doi":"10.1109/ICIG.2011.24","DOIUrl":"https://doi.org/10.1109/ICIG.2011.24","url":null,"abstract":"Various 3D applications require accurate and smooth depth map, and post-processing is necessary for depth map directly generated by different correspondence algorithms. A hierarchical joint bilateral filtering method is proposed to improve the coarse depth map. By first carrying out depth confidence measuring, pixels are put into different categories according to their matching confidence. Then the initial coarse depth map is down-sampled together with the corresponding confidence map. Depth map is progressively fixed during multistep up sampling. Different from many filtering approaches, confident matches are propagated to unconfident regions by suppressing outliers in a hierarchical structure. Experiment results present that the proposed method can achieve significant improvement of initial depth map with low computational complexity.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123491568","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: 11
Metrics for Objective Evaluation of Background Subtraction Algorithms 客观评价背景减法算法的指标
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.163
Leyuan Liu, N. Sang
{"title":"Metrics for Objective Evaluation of Background Subtraction Algorithms","authors":"Leyuan Liu, N. Sang","doi":"10.1109/ICIG.2011.163","DOIUrl":"https://doi.org/10.1109/ICIG.2011.163","url":null,"abstract":"Although a large number of background subtraction (BS) algorithms have been proposed, relevant objective metrics for evaluating these algorithms are still lacking. In this paper, empirical discrepancy metrics, which quantify the spatial accuracy and temporal stability of estimated masks by taking into account the potential inaccuracy of reference masks, the location of the pixel errors relative to the border of reference masks as well as the type of errors, are presented for evaluating the performance of BS algorithms. To validate the proposed metrics, they are applied to tune the optimal parameters of LBP-based background subtraction algorithm, and the experimental results confirm the efficiency of them.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121329832","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: 4
A Novel Algorithm for Ship Detection Based on Dynamic Fusion Model of Multi-feature and Support Vector Machine 基于多特征动态融合模型和支持向量机的船舶检测新算法
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.147
Yu Xia, Shouhong Wan, Lihua Yue
{"title":"A Novel Algorithm for Ship Detection Based on Dynamic Fusion Model of Multi-feature and Support Vector Machine","authors":"Yu Xia, Shouhong Wan, Lihua Yue","doi":"10.1109/ICIG.2011.147","DOIUrl":"https://doi.org/10.1109/ICIG.2011.147","url":null,"abstract":"Ship detection is one of the most important applications of target recognition based on optical remote sensing images. In this paper, we propose an uncertain ship target extraction algorithm based on dynamic fusion model of multi-feature and variance feature of optical remote sensing image. We choose several geometrical features, such as length, wide, rectangular ratio, tightness ratio and so on, using SVM to train and predict the uncertain ship targets extracted by our algorithm automatically. Experiments show that our algorithm is very robust, and the recognition rate of our algorithm can reach or even better than 95%, with the false alarm rate is kept at 3%.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"14 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113975861","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: 33
Diversifying the Image Relevance Reranking with Absorbing Random Walks 吸收随机游走的图像相关性重排序方法
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.113
Zhong Ji, Yuting Su, Yanwei Pang, Xiaojie Qu
{"title":"Diversifying the Image Relevance Reranking with Absorbing Random Walks","authors":"Zhong Ji, Yuting Su, Yanwei Pang, Xiaojie Qu","doi":"10.1109/ICIG.2011.113","DOIUrl":"https://doi.org/10.1109/ICIG.2011.113","url":null,"abstract":"Image visual reranking holds the simple search mechanism preferred by typical users, and exploits the visual information and image analysis methods in another way. Therefore, it integrates characteristics of real-time and accuracy, and has great importance to establish practical image search system. A novel reranking method named DIRRA is proposed in this paper, in which absorbing random walks is utilized to enhance the diversity as well as relevance of the initial search results. Four kinds of image visual features are extracted firstly, and then a graph is built, where nodes are images and edges are the similarities between images. Next, the first item is decided by teleporting random walks on the graph, and the other items are decided by absorbing random walks on the graph at last. Experiments are performed on a web image database including 10 queries, which prove the reranking results are both diverse and relevant, and practical to improve user's satisfaction in web search.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114831612","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: 7
Fast Local Scale Control Based Blur Edge Detection 基于快速局部尺度控制的模糊边缘检测
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.29
Yuan Wu, Weifeng Wu, Qian Huang, Xiaoli Dong
{"title":"Fast Local Scale Control Based Blur Edge Detection","authors":"Yuan Wu, Weifeng Wu, Qian Huang, Xiaoli Dong","doi":"10.1109/ICIG.2011.29","DOIUrl":"https://doi.org/10.1109/ICIG.2011.29","url":null,"abstract":"Extracting objects with blurred edges from inhomogeneous background in the natural images is still under exploring. To locate blurred edges, a fault-tolerant method is adopted in the algorithm, to establish the unique, locally calculable minimum reliable scale for each pixel of the image. By simplifying the process of calculating the second derivation for each pixel, the convolution mask along its gradient direction is used. The calculation complexity of second derivation calculation in the gradient direction is reduced by combining the local scale control with LoG algorithm. Different algorithms are roughly benchmarked in the experiments among three different kinds of typical blurred images. The results show that the proposed algorithm localizes and extracts the blurred edges precisely, moreover it runs fast enough to perform some kind of real-time applications.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"15 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127645133","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: 0
Saliency Detection: A Self-Adaption Sparse Representation Approach 显著性检测:一种自适应稀疏表示方法
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.189
Gaoxiang Zhang, F. Jiang, Debin Zhao, Xiaoshuai Sun, Shaohui Liu
{"title":"Saliency Detection: A Self-Adaption Sparse Representation Approach","authors":"Gaoxiang Zhang, F. Jiang, Debin Zhao, Xiaoshuai Sun, Shaohui Liu","doi":"10.1109/ICIG.2011.189","DOIUrl":"https://doi.org/10.1109/ICIG.2011.189","url":null,"abstract":"Saliency detection is essential to visual attention modelling and various computer vision tasks. Representation and measurement are two important issues for saliency models. Good representation and reasonable measurement are both critical issues in modelling visual saliency mechanism. For every input image, we obtain a self-adaptive dictionary that describes the image content effectively and image prior that forces sparsity in every location in the image using the K-SVD algorithm. For saliency measurement, background firing rate (BFR) is defined for each sparse features and it is followed by feature activation rate (FAR) computation to measure the bottom-up visual saliency.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130182836","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: 0
Image Annotation with Multiple Quantization 基于多重量化的图像标注
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.15
Qiaojin Guo, Ning Li, Yubin Yang, Gangshan Wu
{"title":"Image Annotation with Multiple Quantization","authors":"Qiaojin Guo, Ning Li, Yubin Yang, Gangshan Wu","doi":"10.1109/ICIG.2011.15","DOIUrl":"https://doi.org/10.1109/ICIG.2011.15","url":null,"abstract":"Image annotation plays an important role in image retrieval and understanding. Various techniques have been proposed for assigning keywords to images. One of the most frequently used methods is to search annotated images with similar visual features, and keywords are transfered to new coming images. This leads to the problem of nearest neighbor search, which is a hot topic of pattern recognition, information retrieval, and data compression. In this paper we proposed a fast and effective method for retrieving similar images from large collections of annotated images. The proposed technique employs discrete cosine transform and regular lattice quantization to encode images and search similar images directly with the corresponding codes. This technique is evaluated on image annotation. Similar images are retrieved by utilizing our encoding strategy, and keywords are assigned by utilizing traditional label transfer mechanism. Experimental results show that our method provides competitive performance with traditional methods, and mean while provides one scalable framework for annotating large collections of image dataset.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134221953","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: 0
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