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2013 Seventh International Conference on Image and Graphics最新文献

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TOF Depth Map Super-resolution Using Compressive Sensing 基于压缩感知的TOF深度图超分辨率
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.33
Liwen Liu, Yang Li, Lianghao Wang, Dongxiao Li, Ming Zhang
{"title":"TOF Depth Map Super-resolution Using Compressive Sensing","authors":"Liwen Liu, Yang Li, Lianghao Wang, Dongxiao Li, Ming Zhang","doi":"10.1109/ICIG.2013.33","DOIUrl":"https://doi.org/10.1109/ICIG.2013.33","url":null,"abstract":"Although Time-of-Flight (TOF) camera can provide real-time depth information from a real scene, the resolution of depth map captured by TOF camera is rather limited compared to HD color cameras, and thus it cannot be directly used in 3D reconstruction. In order to handle this problem, this paper proposes a novel compressive sensing (CS) based depth map super-resolution method, which transforms a low resolution depth map to a high resolution depth map. Different from previous depth map SR methods, this algorithm uses a model-based CS as reconstruction theory, and this method also builds a TOF camera sampling model which is used in depth map SR. Experimental results show that the proposed method outperforms state-of-the-art methods for depth map super-resolution.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122085964","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
Performance Comparison of ESVM and CSVM for Classifying the Lung Nodules on CT Scans ESVM与CSVM在CT肺结节分类中的性能比较
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.87
Jing Zhang, M. Cao, Wendong Gai, Bin Li
{"title":"Performance Comparison of ESVM and CSVM for Classifying the Lung Nodules on CT Scans","authors":"Jing Zhang, M. Cao, Wendong Gai, Bin Li","doi":"10.1109/ICIG.2013.87","DOIUrl":"https://doi.org/10.1109/ICIG.2013.87","url":null,"abstract":"The nodules and the multiple times larger non-nodules of the regions of interested(ROIs) in lung areas are achieved, that would lead to a serious imbalance on the sample data. Many scholars have proposed some algorithms to solve this problem. In this paper, in order to guarantee that there is no correlation among the extracted characteristics, the PCA method is adopted to optimize and reduce dimensions, and then the modified support vector machine(SVM) classifiers using the sequential minimal optimization(SMO) algorithm and the grid research method are proposed to improve the computing efficiency. Furthermore, the abundant lung CT images from the hospital partnership could confirm the experimental results. We compare the classification performance between the ensemble SVM(ESVM) classifier and the cost-sensitive SVM(CSVM) classifier to deal with this problem. Experimental results show the performance of the CSVM classifier based on grid search is satisfactory than the ESVM.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124800913","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
Expressive Image Sketching with Two-Layer Image Features 基于双层图像特征的表达性图像素描
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.187
Bo Jiang, Shuyu Liu
{"title":"Expressive Image Sketching with Two-Layer Image Features","authors":"Bo Jiang, Shuyu Liu","doi":"10.1109/ICIG.2013.187","DOIUrl":"https://doi.org/10.1109/ICIG.2013.187","url":null,"abstract":"The paper presents a framework for automatically natural image sketching, motivated by imitating the human line drawing process. The algorithm consists of two steps: sketch extraction and sketch rendering, using the recent computer vision and graphics techniques. In the first step, we design a bottom-up filter bank (low-level features) to propose sketch strength, position and orientation, and then trace and complete sketch following Gestalt laws (middle-level cues). In the second step, each sketch is rendered using a sketch-stroke model, accounting for the length, smoothness, width, and profile strength. Experimental results demonstrate the proposed approach is able to generate expressive sketch paintings from natural images.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130996966","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: 2
Pathological Image Retrieval for Breast Cancer with pLSA Model 应用pLSA模型检索乳腺癌病理图像
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.131
Jun Shi, Yibing Ma, Zhi-guo Jiang, Haoxiang Feng, Jin Chen, Yu Zhao
{"title":"Pathological Image Retrieval for Breast Cancer with pLSA Model","authors":"Jun Shi, Yibing Ma, Zhi-guo Jiang, Haoxiang Feng, Jin Chen, Yu Zhao","doi":"10.1109/ICIG.2013.131","DOIUrl":"https://doi.org/10.1109/ICIG.2013.131","url":null,"abstract":"Pathological image retrieval contributes to computer-aided diagnosis for breast cancer due to the fact that the retrieval results generally contain detailed diagnostic information (e.g. abnormal regions and diagnostic opinion from other doctors) which can offer some reference and assistance to the doctor during diagnosis process. In this paper, we present a novel pathological image retrieval approach based on probabilistic latent semantic analysis (pLSA) model. The method respectively utilizes SIFT features after visual saliency detection, and block Gabor features for the construction of two semantic codebooks, which not only can characterize the salient local invariant features and texture information under different scales and orientations in the pathological images, but also consider the high-level semantic features. Furthermore, we apply pLSA model to discover the latent topics in each codebook. Finally each pathological image is represented by the combination of topics from these two codebooks. The proposed method is evaluated on the pathological image database for breast cancer, which includes 5 categories (mucinous cystadenocarcinoma, invasive lobular carcinoma, basal-like carcinoma, invasive breast cancer and low-grade adenosquamous carcinoma) and 110 cases for each category. Experimental results demonstrate the feasibility and effectiveness of our method.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"23 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131307674","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
All-in-Focus Image Reconstruction Based on Plenoptic Cameras 基于全光学相机的全焦图像重建
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.127
Liu Peng, Liu Dijun
{"title":"All-in-Focus Image Reconstruction Based on Plenoptic Cameras","authors":"Liu Peng, Liu Dijun","doi":"10.1109/ICIG.2013.127","DOIUrl":"https://doi.org/10.1109/ICIG.2013.127","url":null,"abstract":"The depth of field (DoF) in photography is limited by the aperture size and focal length. When the focal length is definite, large aperture size leads to small DoF. In dark scene, we use a large aperture at the cost of deep DoF. The paper gives a detailed analysis of the focused plenoptic camera mode presented by Georgiev and Lumsdaine, and proposes a novel reconstruction algorithm. It recovers the image from radiance samples captured on the sensor and can get images of extended DoF to all-in-focus even with large aperture size. Beside, it can change the angle of view after the exposure. Depth of field of the rendered photo in this algorithm is also studied. The simulation result shows that under the assist of new algorithm, the DoF can be extended greatly.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114101269","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: 6
A Novel Illumination Normalization Algorithm 一种新的光照归一化算法
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.22
Xiaoliang Sun, Xiaolin Liu, Y. Shang
{"title":"A Novel Illumination Normalization Algorithm","authors":"Xiaoliang Sun, Xiaolin Liu, Y. Shang","doi":"10.1109/ICIG.2013.22","DOIUrl":"https://doi.org/10.1109/ICIG.2013.22","url":null,"abstract":"This paper studies the illumination normalization of images which are captured under complex lighting condition and analyses the problems of halo and gradient reversal exist in traditional techniques theoretically. Based on the weighted least square filter (WLS), this paper proposes a new illumination normalization algorithm. The proposed algorithm gets the accurate estimation of the illumination of the image by using the weighted least square filter and then eliminates the effects brought by light changing, it also enhances the contrast adaptively by using the modified S function. Experiment results show that the proposed algorithm can eliminates the degradation caused by light changing drastically and improves the post processing algorithms' performances effectively.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"315 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125078162","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
A New Training Principle for Stacked Denoising Autoencoders 叠置去噪自编码器的一种新的训练原理
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.83
Qianhaozhe You, Yujin Zhang
{"title":"A New Training Principle for Stacked Denoising Autoencoders","authors":"Qianhaozhe You, Yujin Zhang","doi":"10.1109/ICIG.2013.83","DOIUrl":"https://doi.org/10.1109/ICIG.2013.83","url":null,"abstract":"In this work, a new training principle is introduced for unsupervised learning that makes the learned representations more efficient and useful. Using partially corrupted inputs instead, the denoising Auto encoder can obtain more robust and representative pattern of inputs than the traditional learning methods. Besides, this denoising Auto encoder can be stacked to form a deep network. The whole framework of training stacked denoising Auto encoders, which involved several supervised training methods in the framework, is given for image classification. Comparative experiments have shown that the model can resist noise of training examples powerfully and achieve better accuracy of image classification on MNIST database.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122594584","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: 5
An Adaptive Non-local Means Filter Based on Region Homogeneity 基于区域均匀性的自适应非局部均值滤波
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.16
Xia Lan, Huanfeng Shen, Liangpei Zhang
{"title":"An Adaptive Non-local Means Filter Based on Region Homogeneity","authors":"Xia Lan, Huanfeng Shen, Liangpei Zhang","doi":"10.1109/ICIG.2013.16","DOIUrl":"https://doi.org/10.1109/ICIG.2013.16","url":null,"abstract":"In this paper, a local scale measure is presented for the detection of homogeneous regions in an image. Then, based on region homogeneity, an adaptive nonlocal means filter (ANLMF) is proposed. In this method, the neighborhood window size for denoising varies adaptively, according to the local scale measure. Experiments show that the proposed filter (ANLMF) is better than the state-of-the-art nonlocal means filter (NLMF).","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131541871","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
Unstructured Synthetic Aperture Photograph Based Occluded Object Imaging 基于非结构合成孔径照片的遮挡物成像
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.13
Wenguang Ma, Tao Yang, Yanning Zhang, Xiao-min Tong
{"title":"Unstructured Synthetic Aperture Photograph Based Occluded Object Imaging","authors":"Wenguang Ma, Tao Yang, Yanning Zhang, Xiao-min Tong","doi":"10.1109/ICIG.2013.13","DOIUrl":"https://doi.org/10.1109/ICIG.2013.13","url":null,"abstract":"Recently the camera array synthetic aperture imaging has been proved to be a powerful technology for occluded object imaging. However, synthetic aperture imaging with a camera mounted on a moving platform is still a significant challenging task for many computer vision applications. This paper presents a novel unstructured synthetic aperture imaging approach to solve the above problem. The main characteristics of our approach include: (1) To the best of our knowledge, our proposed method is the first one for synthetic aperture imaging through occlusion on a moving platform. (2) In contrast to \"averaging data\", we creatively use the clustering method to estimate the pixel color with high visible probability in the virtual focal plane. A new moving synthetic aperture imaging system has been built to capture unstructured light field in complex outdoor scene, and experimental results demonstrate that our approach successfully generates clear image of hidden object even under severe occlusion, which outperform the traditional synthetic aperture imaging method.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132932567","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 Construction Model for 3D Imaging of Scanning Acoustic Microscopy 扫描声显微镜三维成像的构建模型
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.6
Ding Jinwen, He Guochao, L. Kang, Dong Lanfang, Yao Chuanming, Li Feng
{"title":"A Construction Model for 3D Imaging of Scanning Acoustic Microscopy","authors":"Ding Jinwen, He Guochao, L. Kang, Dong Lanfang, Yao Chuanming, Li Feng","doi":"10.1109/ICIG.2013.6","DOIUrl":"https://doi.org/10.1109/ICIG.2013.6","url":null,"abstract":"The paper proposal a model of square column, which consist of the data of echo signal pattern extracted from volume database, to construct the imaging cube and depict the micro internal boundaries in it, to realize three-dimensional (3D) visualization in full direction, for the application of scanning acoustic microscopy (SAM) to evaluate the internal defects in bulk specimen. The results show that 3D acoustical visualization presents more affluent, overall view and intuitive pattern than 2D imaging for micro-sized structure investigation.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134301196","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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