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2009 Second International Conference on Machine Vision最新文献

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Marathi Language Speech Synthesizer Using Concatenative Synthesis Strategy (Spoken in Maharashtra, India) 使用串联合成策略的马拉地语语音合成器(在印度马哈拉施特拉邦使用)
2009 Second International Conference on Machine Vision Pub Date : 2009-12-28 DOI: 10.1109/ICMV.2009.52
S. Shirbahadurkar, D. Bormane
{"title":"Marathi Language Speech Synthesizer Using Concatenative Synthesis Strategy (Spoken in Maharashtra, India)","authors":"S. Shirbahadurkar, D. Bormane","doi":"10.1109/ICMV.2009.52","DOIUrl":"https://doi.org/10.1109/ICMV.2009.52","url":null,"abstract":"in this paper, we present the concatenative text-to-speech system and discuss the issues relevant to the development of a Marathi speech synthesizer using different choice of units: words, phonemes as a database. Quality of the synthesizer with different unit size indicates that the word synthesizer performs better than the phoneme synthesizer. The most important qualities of a speech synthesis system are naturalness and intelligibility. We synthesize the Marathi text and perform the subjective evaluations of the synthesized speech. As a result, (1) 81% of speech synthesized by the proposed method was preferred to that by the conventional method, (2) The error rate of TTS synthesizer is around 8.22%, (3) Speech synthesis runtime was reduced for proposed method. The results show the effectiveness of the proposed method.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116695548","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: 12
Compare between Several Linear Image Edge Detection Algorithm 几种线性图像边缘检测算法的比较
2009 Second International Conference on Machine Vision Pub Date : 2009-12-28 DOI: 10.1109/ICMV.2009.77
Song Qiang, Lingxia Liu
{"title":"Compare between Several Linear Image Edge Detection Algorithm","authors":"Song Qiang, Lingxia Liu","doi":"10.1109/ICMV.2009.77","DOIUrl":"https://doi.org/10.1109/ICMV.2009.77","url":null,"abstract":"Along with the rapid development of computer technology, image edge detection has become an important content of image processing. It is the basic problem of image analysis as well as the premise of image segmentation, feature extraction and image recognition. This paper discusses in detail two edge detection algorithms based on linear filtering technique, namely Marr-Hildreth algorithm and Canny algorithm.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125015899","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
Improved Kernel Common Vector Method for Face Recognition 改进的核公共向量人脸识别方法
2009 Second International Conference on Machine Vision Pub Date : 2009-12-28 DOI: 10.1007/978-3-642-12712-0_16
C. Lakshmi, Dr. M. Ponnavaikko, Dr. M. Sundararajan
{"title":"Improved Kernel Common Vector Method for Face Recognition","authors":"C. Lakshmi, Dr. M. Ponnavaikko, Dr. M. Sundararajan","doi":"10.1007/978-3-642-12712-0_16","DOIUrl":"https://doi.org/10.1007/978-3-642-12712-0_16","url":null,"abstract":"","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116759318","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: 44
Binarization of Documents with Complex Backgrounds 复杂背景文档的二值化
2009 Second International Conference on Machine Vision Pub Date : 2009-12-28 DOI: 10.1109/ICMV.2009.9
A. Rao, T. Sreenivasu, N. V. Rao, A. Sastry, L. Reddy, T. K. Prabhu
{"title":"Binarization of Documents with Complex Backgrounds","authors":"A. Rao, T. Sreenivasu, N. V. Rao, A. Sastry, L. Reddy, T. K. Prabhu","doi":"10.1109/ICMV.2009.9","DOIUrl":"https://doi.org/10.1109/ICMV.2009.9","url":null,"abstract":"In this paper, a novel heuristic based approach adopted from George D.C. Calvacanti algorithm for removing background noise from all types of images with complex background is presented. In this approach Binarization is done by selecting two threshold values, one for foreground and another for background for the separation. Morphological techniques are used for improving the quality of the resultant image. In addition to this PSNR ratio is calculated for all the images and its variation with respect to the intensity of the background noise is observed.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133586710","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
Improvement of Connectivity in Mobile Ad Hoc Networks by Adding Static Nodes Based on a Realistic Mobility Model 基于现实移动模型的增加静态节点改善移动Ad Hoc网络连通性
2009 Second International Conference on Machine Vision Pub Date : 2009-12-28 DOI: 10.1109/ICMV.2009.56
Morteza Romoozi, S. M. Vahidipour, H. Babaei
{"title":"Improvement of Connectivity in Mobile Ad Hoc Networks by Adding Static Nodes Based on a Realistic Mobility Model","authors":"Morteza Romoozi, S. M. Vahidipour, H. Babaei","doi":"10.1109/ICMV.2009.56","DOIUrl":"https://doi.org/10.1109/ICMV.2009.56","url":null,"abstract":"One of the ad-hoc networks challenges is the connectivity problem coming from changeable and dynamic topology of networks nodes. According to most of researches done on this problem, one of the solutions is adding static nodes in some points in network environment; and many attempts have been made to find these points by using different ways. However, in most of these studies no attention has been paid to network mobility model or the problem has been solved based on unrealistic mobility model such as Random waypoint. Thus previous works are not applicable in reality. This article presents an algorithm for adding static nodes which are located in best points of network to improve connectivity. This algorithm is based on realistic mobility model that can model both environmental obstacles and pathways, and furthermore can describe the realistic movement pattern of the nodes. Proposed algorithm uses Genetic algorithm to find the best points. Since simulation operation for evaluation of solution is time-consuming, this algorithm is independent from simulation operation and uses Voronoi diagram.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132233564","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: 10
Discriminative Models-Based Hand Gesture Recognition 基于判别模型的手势识别
2009 Second International Conference on Machine Vision Pub Date : 2009-12-28 DOI: 10.1109/ICMV.2009.29
M. Elmezain, A. Al-Hamadi, B. Michaelis
{"title":"Discriminative Models-Based Hand Gesture Recognition","authors":"M. Elmezain, A. Al-Hamadi, B. Michaelis","doi":"10.1109/ICMV.2009.29","DOIUrl":"https://doi.org/10.1109/ICMV.2009.29","url":null,"abstract":"In this paper, we study the discriminative models like CRFs, HCRFs and LDCRFs to recognize alphabet characters (A-Z) and numbers (0-9) in real-time from stereo color image sequences. To handle isolated gesture, CRFs, HCRFs and LDCRFs with different number of window size are applied on 3D combined features of location, orientation and velocity. The gesture recognition rate is improved initially as the window size increase, but degrades as window size increase further. In contrast to generative approaches such as HMMs, experimental results show that the LDCRFs are the best in terms of results than CRFs, HCRFs and HMMs at window size equal 4. Additionally, our results show that; an overall recognition rates are 91.52%, 95.28% and 98.05% for CRFs, HCRFs, and LDCRFs respectively.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133059983","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: 14
Multi-user Interaction in Collaborative Augmented Reality for Urban Simulation 城市模拟协同增强现实中的多用户交互
2009 Second International Conference on Machine Vision Pub Date : 2009-12-28 DOI: 10.1109/ICMV.2009.40
A. W. Ismail, M. S. Sunar
{"title":"Multi-user Interaction in Collaborative Augmented Reality for Urban Simulation","authors":"A. W. Ismail, M. S. Sunar","doi":"10.1109/ICMV.2009.40","DOIUrl":"https://doi.org/10.1109/ICMV.2009.40","url":null,"abstract":"Augmented reality (AR) environment allows user or multi-user to interact with 2D and 3D data. AR simply can provide a collaborative interactive AR environment for urban simulation, where users can interact naturally and intuitively. AR collaboration approach can be effectively used to develop different interfaces for face-to-face and remote collaboration. This is because AR provides seamless interaction between real and virtual environments, the ability to enhance reality, the presence of spatial cues for face-to-face and remote collaboration, support of a tangible interface metaphor, the ability to transition smoothly between reality and virtuality. In addition, the collaborative AR makes multi-user in urban simulation to share simultaneously a real world and virtual world. The fusion between real and virtual world, existed in AR environment by see-through HMDs, achieves higher interactivity as a key features of collaborative AR. In real-time, precise registration between both worlds and multi-user are crucial for the collaborations. Collaborative AR approach allows multi-user to simultaneously share a real world surrounding them and a virtual world. Common problems in AR environment will be discussed and major issues in collaborative AR will be explained details in this survey. The features of collaboration in AR environment are will be identified and the requirements of collaborative AR will be defined. This paper will give an overview on collaborative AR environment for multi-user in urban studies and planning. The work will also cover numerous systems of collaborative AR environments for multi-user.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122889729","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
Impact of Feature Selection on Support Vector Machine Using Microarray Gene Expression Data 基于微阵列基因表达数据的特征选择对支持向量机的影响
2009 Second International Conference on Machine Vision Pub Date : 2009-12-28 DOI: 10.1109/ICMV.2009.46
C. Wahid, A. Ali, K. Tickle
{"title":"Impact of Feature Selection on Support Vector Machine Using Microarray Gene Expression Data","authors":"C. Wahid, A. Ali, K. Tickle","doi":"10.1109/ICMV.2009.46","DOIUrl":"https://doi.org/10.1109/ICMV.2009.46","url":null,"abstract":"Recent researches have investigated the impact of feature selection methods on the performance of support vector machine (SVM) and claimed that no feature selection methods improve it in high dimension. However, they have based this argument on their experiments with simulated data. We have taken this claim as a research issue and investigated different feature selection methods on the real time micro array gene expression data. Our research outcome indicates that feature selection methods do have a positive impact on the performance of SVM in classifying micro array gene expression data.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126011004","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
Pruned Associative Classification Technique for the Medical Image Diagnosis System 医学图像诊断系统的剪枝关联分类技术
2009 Second International Conference on Machine Vision Pub Date : 2009-12-28 DOI: 10.1109/ICMV.2009.55
P. Rajendran, M. Madheswaran
{"title":"Pruned Associative Classification Technique for the Medical Image Diagnosis System","authors":"P. Rajendran, M. Madheswaran","doi":"10.1109/ICMV.2009.55","DOIUrl":"https://doi.org/10.1109/ICMV.2009.55","url":null,"abstract":"Brain tumor is one of the leading cause of death in recent years. This paper proposes the tumor detection in CT scan brain images, which can assist the medical image diagnosis system. The method proposed here makes use of association rule mining technique to classify the CT scan brain images. It combines the low-level features extracted from images and high level knowledge from specialists. The proposed system consists of: a pre-processing phase, feature extraction phase, a phase for mining the resultant transaction database, a final phase to build the classifier and generating the suggestion of diagnosis. The classifier built in this method has an important characteristic that it can suggest multiple keywords per image, which improves the accuracy. Experimental results on pre-diagnosed database of brain images shows high accuracy (up to 95%), allowing us to claim that the use of associative classifier is an efficient technique to assist in the diagnosing task.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124192738","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: 18
Adaptive Binarization of Ancient Documents 古代文献的自适应二值化
2009 Second International Conference on Machine Vision Pub Date : 2009-12-28 DOI: 10.1109/ICMV.2009.8
A. Rao, Golla Sunil, N. V. Rao, T. K. Prabhu, L. Reddy, A. Sastry
{"title":"Adaptive Binarization of Ancient Documents","authors":"A. Rao, Golla Sunil, N. V. Rao, T. K. Prabhu, L. Reddy, A. Sastry","doi":"10.1109/ICMV.2009.8","DOIUrl":"https://doi.org/10.1109/ICMV.2009.8","url":null,"abstract":"It is common for libraries to provide public access to historical and ancient document image collections. Such document images to require specialized processing in order to remove background noise and become more legible. In this paper the proposed approach is adapted from the kavallieratov’s algorithm for cleaning background noise from the ancient documents by iterative global thresholding and local thresholding technique. Finally the image quality is enhanced by using morphological technique and compared with other methods in the process of cleaning.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125391930","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
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