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2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics最新文献

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A Fast Interactive Image Segmentation to Locate Multiple Similar-colored Objects 一种快速交互式图像分割方法定位多个相似颜色的目标
2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics Pub Date : 2011-12-15 DOI: 10.1109/NCVPRIPG.2011.13
B. Dhara, B. Chanda
{"title":"A Fast Interactive Image Segmentation to Locate Multiple Similar-colored Objects","authors":"B. Dhara, B. Chanda","doi":"10.1109/NCVPRIPG.2011.13","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2011.13","url":null,"abstract":"A fundamental problem in image processing is image segmentation. The conventional image segmentation methods, to some extent, all suffe from the problem of inaccurate segmentation. A slightly easier and more approachable problem -- interactive segmentation -- has also received a lot of attentions over the years. In this paper, we propose a fast and simple interactive image segmentation technique. This segmentation process is conducted in two modules. First, the original image is pre-segmented by a low level segmentation method. Second, some portion of the object-of-interest is marked. The proposed method identifies all the similar-colored objects present in the image. In this work, color feature is used to measure the closeness between two regions and accordingly the label of the unmarked region is decided.","PeriodicalId":285162,"journal":{"name":"2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics","volume":"C-23 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121004918","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
Local Ternary Patterns and Maximum Bipartite Matching for Face Recognition 人脸识别的局部三元模式和最大二部匹配
2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics Pub Date : 2011-12-15 DOI: 10.1109/NCVPRIPG.2011.41
Renuka Patnaik, Raj Gupta, Anurag Mittal
{"title":"Local Ternary Patterns and Maximum Bipartite Matching for Face Recognition","authors":"Renuka Patnaik, Raj Gupta, Anurag Mittal","doi":"10.1109/NCVPRIPG.2011.41","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2011.41","url":null,"abstract":"Local Binary Pattern (LBP) has been the successful feature descriptor used for face recognition. The basic idea in this method is to convert from an intensity space to an order space where the order of neighboring pixels is used to create a monotonic change illumination-invariant code for each point in the image. A drawback for this method, however, is that, in homogenous regions, the order of the pixel with respect to its neighbors is quite noisy. In this paper, we propose to use a third value which indicates if two pixels are similar in value. We also propose to match these patterns using maximum bipartite matching rather than histogram matching. Significant performance boost was found when compared to LBP and other standard methods like Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). We present our results on Extended Yale and FERET datasets.","PeriodicalId":285162,"journal":{"name":"2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125239483","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
Recursive Computation of Forward Krawtchouk Moment Transform Using Clenshaw's Recurrence Formula 用克伦肖递推公式递推正演克劳丘克矩变换
2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics Pub Date : 2011-12-15 DOI: 10.1109/NCVPRIPG.2011.66
A. Venkataramana, P. A. Raj
{"title":"Recursive Computation of Forward Krawtchouk Moment Transform Using Clenshaw's Recurrence Formula","authors":"A. Venkataramana, P. A. Raj","doi":"10.1109/NCVPRIPG.2011.66","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2011.66","url":null,"abstract":"Forward Krawtchouk moment transform (FKMT) needs more computations when a straightforward method of computation is chosen. Hence, this paper proposes a simple recursive method to reduce the number of computations using a Clenshaw's recurrence formula. Further, it is also shown that the number of computations can still be reduced by using the symmetry property of weighted Krawtchouk polynomials that are used to define FKMT. The proposed approach is verified with theoretical calculations as well as CPU time required for computation of FKMT of 1D and 2D points. The obtained recursive structure is simple and modular, Hence, it is suitable for parallel VLSI implementation.","PeriodicalId":285162,"journal":{"name":"2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122597363","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
Building a Natural Language Hindi Speech Interface to Access Market Information 建立一个自然语言印地语语音接口来获取市场信息
2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics Pub Date : 2011-12-15 DOI: 10.1109/NCVPRIPG.2011.20
A. Imran, Sunil Kumar Kopparapu
{"title":"Building a Natural Language Hindi Speech Interface to Access Market Information","authors":"A. Imran, Sunil Kumar Kopparapu","doi":"10.1109/NCVPRIPG.2011.20","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2011.20","url":null,"abstract":"It is a well known fact that majority of rural India earns its livelihood from agriculture and farming. Although India is a net exporter of various agricultural products, the farmer who happens to be the primary producer, has remained information poor which puts him at a disadvantage. With little or no knowledge of prices at the markets, farmers have no leverage to negotiate better prices for their produce. Speech based solution can address this issue of market price information availibility to farmers. Speech based solutions are increasingly being used for transaction but they are both (a) restricted to menu based type interactions where a series of interactions are required for the transaction to take place and (b) primarily built for the English literate population synonymously urban population. Paradoxically, the benefit of a speech based solution is best reaped by the rural folks speaking their native language (very often non-English) because the other modes of transactions are either not readily available to them or if available difficult to use. In this paper, we develop a natural language Hindi speech interface to enable Hindi speaking population access market prices of commodities.","PeriodicalId":285162,"journal":{"name":"2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131886953","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
Music Genre Classification Using GA-Induced Minimal Feature-Set 使用ga诱导的最小特征集进行音乐类型分类
2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics Pub Date : 2011-12-15 DOI: 10.1109/NCVPRIPG.2011.61
S. Nayak, Ankit Bhutani
{"title":"Music Genre Classification Using GA-Induced Minimal Feature-Set","authors":"S. Nayak, Ankit Bhutani","doi":"10.1109/NCVPRIPG.2011.61","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2011.61","url":null,"abstract":"We propose a genetic algorithm-based feature-selection method for music genre classification that not only increases the efficiency of standard classifiers, but also reduces the feature space to a bare-minimum. While previous works have been more focused on finding near-optimal features devoid of noise, we go for a modified fitness function capable of finding both the near-optimal and the near-minimal feature subset for classification. In addition to an enhanced performance, our model can also reduce the computational load for ill-formed sets and has the flexibility to incorporate trade-offs between efficiency and computational load. We finally demonstrate that the modified GA is capable of bringing about an 80% reduction in the feature space dimension at similar classification rates.","PeriodicalId":285162,"journal":{"name":"2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131962263","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
An Entropic Score to Rank Annotators for Crowdsourced Labeling Tasks 为众包标注任务排序标注者的熵值
2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics Pub Date : 2011-12-15 DOI: 10.1109/NCVPRIPG.2011.14
V. Raykar, Shipeng Yu
{"title":"An Entropic Score to Rank Annotators for Crowdsourced Labeling Tasks","authors":"V. Raykar, Shipeng Yu","doi":"10.1109/NCVPRIPG.2011.14","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2011.14","url":null,"abstract":"With the advent of crowd sourcing services it has become quite cheap and reasonably effective to get a dataset labeled by multiple annotators in a short amount of time. Various methods have been proposed to estimate the consensus labels by correcting for the bias of annotators with different kinds of expertise. Often we have low quality annotators or spammers -- annotators who assign labels randomly (e.g., without actually looking at the instance). Spammers can make the cost of acquiring labels very expensive and can potentially degrade the quality of the consensus labels. In this paper we propose a score (based on the reduction in entropy) which can be used to rank the annotators -- with the spammers having a score close to zero and the good annotators having a high score close to one.","PeriodicalId":285162,"journal":{"name":"2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129161575","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: 26
Camera and Light Source Placement: A Multi-Objective Approach 相机和光源放置:多目标方法
2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics Pub Date : 2011-12-15 DOI: 10.1109/NCVPRIPG.2011.47
Ritu Garg, S. Indu, S. Chaudhury
{"title":"Camera and Light Source Placement: A Multi-Objective Approach","authors":"Ritu Garg, S. Indu, S. Chaudhury","doi":"10.1109/NCVPRIPG.2011.47","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2011.47","url":null,"abstract":"Optimal placement of visual sensors along with good lighting conditions is indispensable for the successful execution of surveillance applications. Limited field-of-view, depth-of-field, occlusion due to presence of different objects in the scene form the major constraints for visual sensor placement. While over/under exposed objects, shadowing and light rays directly incident on the camera lens are some of the constraints for light source placement. Because of the nature of the constraints and complexity of the problem, the placement problem is considered to be a multi-objective global optimization problem. The paper outlines the camera and light source location optimization problem with multiple objective functions. Multi-Objective Genetic Algorithm is used to maximize the camera coverage with optimum illumination of the sensing space.","PeriodicalId":285162,"journal":{"name":"2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116763817","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
Extraction of Fibrillation Components from Ventricular Arrhythmic Electrocardiograms 室性心律失常心电图中纤颤成分的提取
2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics Pub Date : 2011-12-15 DOI: 10.1109/NCVPRIPG.2011.37
Shreya Das, M. Chakraborty
{"title":"Extraction of Fibrillation Components from Ventricular Arrhythmic Electrocardiograms","authors":"Shreya Das, M. Chakraborty","doi":"10.1109/NCVPRIPG.2011.37","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2011.37","url":null,"abstract":"Presence of fibrillation in electrocardiograms shows distinct peaks in the 3-7 Hz frequency band of its frequency spectrum. In this paper the comparison between the presence of fibrillation component in ECG data before and after QRS detection has been done using digital signal processing techniques. The band pass filtering of these two signals and then their frequency analysis show the prominent peaks in the 3-7 Hz frequency band, detecting fibrillation in the data. But in case of the frequency spectrum of the band pass filtered signal after QRS detection, the required peaks are more prominent and higher in amplitude.","PeriodicalId":285162,"journal":{"name":"2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114769802","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
Detection of Micro-calcification to Characterize Malignant Breast Lesion 微钙化检测对乳腺恶性病变的诊断价值
2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics Pub Date : 2011-12-15 DOI: 10.1109/NCVPRIPG.2011.60
Subarna Chatterjee, A. Ray, Rezaul Karim, A. Biswas
{"title":"Detection of Micro-calcification to Characterize Malignant Breast Lesion","authors":"Subarna Chatterjee, A. Ray, Rezaul Karim, A. Biswas","doi":"10.1109/NCVPRIPG.2011.60","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2011.60","url":null,"abstract":"Worldwide, breast cancer is the fifth most common cause of cancer death and is the most common cancer among women [14]. With advances in screening, diagnosis, and treatment, the death rate for breast cancer has declined by about 20% over the past decade. Micro-calcifications are calcium deposit, which can be identified as tiny areas that are slightly brighter than surrounding tissues [13]. In this paper, we propose a micro-calcification detection algorithm in two parts. One is segmentation of the mass or nodule and the other is detection of micro-calcification within the mass. MATLAB has been used for the simulation of this algorithm and the results obtained are presented in this paper.","PeriodicalId":285162,"journal":{"name":"2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130383816","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
Geometric Attack Invariant Watermarking with Biometric Data - Applied on Offline Handwritten Signature 基于生物特征数据的几何攻击不变性水印——在离线手写签名中的应用
2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics Pub Date : 2011-12-15 DOI: 10.1109/NCVPRIPG.2011.62
S. Geetha, S. Sindhu, S. Priya, S. Mubakiya, N. Kamaraj
{"title":"Geometric Attack Invariant Watermarking with Biometric Data - Applied on Offline Handwritten Signature","authors":"S. Geetha, S. Sindhu, S. Priya, S. Mubakiya, N. Kamaraj","doi":"10.1109/NCVPRIPG.2011.62","DOIUrl":"https://doi.org/10.1109/NCVPRIPG.2011.62","url":null,"abstract":"Biometric watermarking refers to the process of incorporating the handwritten signatures or fingerprints in watermarking technology. In this paper, we present a novel statistical attack invariant watermarking scheme to embed an offline handwritten signature invisibly in the host as a notice of genuine ownership. The scheme employs Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) with Least Significant Bit (LSB) encoding for watermark insertion, which is to be known as DCT-SVD scheme. Experimental results confirm that DCT-SVD scheme is robust to statistical attacks even in the presence of deliberate distortions.","PeriodicalId":285162,"journal":{"name":"2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics","volume":"45 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114271166","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
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