We will be able to use highly parallel processing environments. This paper proposes a method for estimating translations, rotations and scaling reaching 10 times simultaneously based on the multiple scaling assumptions, and represents its performance with motion estimation experiments. A sector region luminosity correlation is used for estimating motion vectors. The sector region luminosity correlation is robust about the rotation and withstands large motion environments. The proposed method makes the assumptions about the scaling and estimates the motion vectors based on the assumptions. Then it randomly creates the pair of the estimated motion vectors. Next, it selects the proper pair using the pre-assumed scaling factor. The selected pairs are included in the set of reliable motion vector pairs. The reliable motion vector pairs decide the translation, rotation and scaling. With large scaling, it is difficult to estimate the motion using the sector region luminosity correlation. But with the assumptions about the scaling, they can work. Experiments show that the proposed method makes much better correlations between images than SIFT does in 10 times scaling changes.
{"title":"Estimation of Translation, Rotation and Large Scale Scaling Based on Multiple Scaling Assumptions","authors":"K. Aoki","doi":"10.1109/ICMV.2009.45","DOIUrl":"https://doi.org/10.1109/ICMV.2009.45","url":null,"abstract":"We will be able to use highly parallel processing environments. This paper proposes a method for estimating translations, rotations and scaling reaching 10 times simultaneously based on the multiple scaling assumptions, and represents its performance with motion estimation experiments. A sector region luminosity correlation is used for estimating motion vectors. The sector region luminosity correlation is robust about the rotation and withstands large motion environments. The proposed method makes the assumptions about the scaling and estimates the motion vectors based on the assumptions. Then it randomly creates the pair of the estimated motion vectors. Next, it selects the proper pair using the pre-assumed scaling factor. The selected pairs are included in the set of reliable motion vector pairs. The reliable motion vector pairs decide the translation, rotation and scaling. With large scaling, it is difficult to estimate the motion using the sector region luminosity correlation. But with the assumptions about the scaling, they can work. Experiments show that the proposed method makes much better correlations between images than SIFT does in 10 times scaling changes.","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":"123452440","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}
In this paper, we present a technique of secure data transmission through hiding of data in audio file by replacing it’s one of the higher 4th layer LSB bit. The. watermarked bit embedded into audio signal increases the robustness against noise
{"title":"Robust & Secure Transmission over Insecure Channel through Higher Level Bit Replacement","authors":"Srikant Burje, S. Dubey, V. Nikam","doi":"10.1109/ICMV.2009.37","DOIUrl":"https://doi.org/10.1109/ICMV.2009.37","url":null,"abstract":"In this paper, we present a technique of secure data transmission through hiding of data in audio file by replacing it’s one of the higher 4th layer LSB bit. The. watermarked bit embedded into audio signal increases the robustness against noise","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"15 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":"116756670","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}
A simulation of a new vibration isolation system using negative stiffness is proposed in this paper. The vibration isolation can be improved by incorporating a negative stiffness such that the dynamic stiffness is much less than the static stiffness. This paper is concerned with the nonlinear analysis using Harmonic Balance (HB) method of a High-Static-Low-Dynamic-Stiffness (HSLDS) system. The system consist of an isolated mass arranged in such a way it is attracted by other magnets located at each spring ends. The computer simulation agrees reasonably well for both Duffing oscillator and HB analysis.
{"title":"Harmonic Balance Simulation for the Nonlinear Analysis of Vibration Isolation System Using Negative Stiffness","authors":"M. Nor, A. H. Abdullah, Alias Mat Saman","doi":"10.1109/ICMV.2009.69","DOIUrl":"https://doi.org/10.1109/ICMV.2009.69","url":null,"abstract":"A simulation of a new vibration isolation system using negative stiffness is proposed in this paper. The vibration isolation can be improved by incorporating a negative stiffness such that the dynamic stiffness is much less than the static stiffness. This paper is concerned with the nonlinear analysis using Harmonic Balance (HB) method of a High-Static-Low-Dynamic-Stiffness (HSLDS) system. The system consist of an isolated mass arranged in such a way it is attracted by other magnets located at each spring ends. The computer simulation agrees reasonably well for both Duffing oscillator and HB analysis.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"1 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":"130590430","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}
Mutual information based image registration has the advantages of high precision and strong robustness. However, the solution of this registration method is easy to fall into the local extremes. To overcome this problem, in this paper we propose a new optimal algorithm for image registration, which combines ant colony algorithm with particle swarm algorithm based on wavelet transform. Experiment results demonstrate our proposed approach effective.
{"title":"Image Registration Using Ant Colony and Particle Swarm Hybrid Algorithm Based on Wavelet Transform","authors":"Aiye Shi, Fengchen Huang, Yang Pan, Lizhong Xu","doi":"10.1109/ICMV.2009.11","DOIUrl":"https://doi.org/10.1109/ICMV.2009.11","url":null,"abstract":"Mutual information based image registration has the advantages of high precision and strong robustness. However, the solution of this registration method is easy to fall into the local extremes. To overcome this problem, in this paper we propose a new optimal algorithm for image registration, which combines ant colony algorithm with particle swarm algorithm based on wavelet transform. Experiment results demonstrate our proposed approach effective.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"50 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":"125249189","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}
This paper describes image fusion in detail, and firstly intrudes the three basic levels which are pixel level, feature level and decision level fusion, and then compares with their properties and all other aspects. Then it describes the evaluation criteria of image fusion results from subjective evaluation and objective evaluation two aspects. According to the quantitative evaluation of the image fusion results and quality, this text uses and defines multiple evaluation parameters such as fusion image entropy, mutual information MI, the average gradient, standard deviation, cross-entropy, unite entropy, bias, relative bias, mean square error, root mean square error and peak SNR, and establishes the corresponding evaluation criteria.
{"title":"Discussion and Analyze on Image Fusion Technology","authors":"T. Hui, W. Binbin","doi":"10.1109/ICMV.2009.71","DOIUrl":"https://doi.org/10.1109/ICMV.2009.71","url":null,"abstract":"This paper describes image fusion in detail, and firstly intrudes the three basic levels which are pixel level, feature level and decision level fusion, and then compares with their properties and all other aspects. Then it describes the evaluation criteria of image fusion results from subjective evaluation and objective evaluation two aspects. According to the quantitative evaluation of the image fusion results and quality, this text uses and defines multiple evaluation parameters such as fusion image entropy, mutual information MI, the average gradient, standard deviation, cross-entropy, unite entropy, bias, relative bias, mean square error, root mean square error and peak SNR, and establishes the corresponding evaluation criteria.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"1 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":"131084838","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}
Detecting pedestrians is a challenging task, which requires precise localization of pedestrians that appear in images and videos. Window-scanning based detection methods have demonstrated their promise by scanning the image densely with multi-scale detection window. However, an essential and critical issue, i.e., how to fuse these dense detections obtained through pedestrian detector and yield the final target detection, is not well addressed in the literature. This paper proposes and implements a general method for fusing pedestrian detections. In this method, detection fusion is regarded as a kernel density estimate and implemented through mean shift iterative procedure. Moreover, the notion of nearest neighbor consistency is adopted, which significantly accelerates the fusion procedure. Experimental results demonstrate the efficiency of the mean shift-based fusion method.
{"title":"Pedestrian Detection Fusion Method Based on Mean Shift","authors":"Liping Yu, Wentao Yao","doi":"10.1109/ICMV.2009.13","DOIUrl":"https://doi.org/10.1109/ICMV.2009.13","url":null,"abstract":"Detecting pedestrians is a challenging task, which requires precise localization of pedestrians that appear in images and videos. Window-scanning based detection methods have demonstrated their promise by scanning the image densely with multi-scale detection window. However, an essential and critical issue, i.e., how to fuse these dense detections obtained through pedestrian detector and yield the final target detection, is not well addressed in the literature. This paper proposes and implements a general method for fusing pedestrian detections. In this method, detection fusion is regarded as a kernel density estimate and implemented through mean shift iterative procedure. Moreover, the notion of nearest neighbor consistency is adopted, which significantly accelerates the fusion procedure. Experimental results demonstrate the efficiency of the mean shift-based fusion method.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"37 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":"133294291","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}
Dakshina Ranjan Kisku, Jamuna Kanta Sing, Phalguni Gupta
This paper proposes a multimodal biometric system through Gaussian Mixture Model (GMM) for face and ear biometrics with belief fusion of the estimated scores characterized by Gabor responses and the proposed fusion is accomplished by Dempster-Shafer (DS) decision theory. Face and ear images are convolved with Gabor wavelet filters to extracts spatially enhanced Gabor facial features and Gabor ear features. Further, GMM is applied to the high-dimensional Gabor face and Gabor ear responses separately for quantitive measurements. Expectation Maximization (EM) algorithm is used to estimate density parameters in GMM. This produces two sets of feature vectors which are then fused using Dempster-Shafer theory. Experiments are conducted on multimodal database containing face and ear images of 400 individuals. It is found that use of Gabor wavelet filters along with GMM and DS theory can provide robust and efficient multimodal fusion strategy.
{"title":"Multibiometrics Belief Fusion","authors":"Dakshina Ranjan Kisku, Jamuna Kanta Sing, Phalguni Gupta","doi":"10.1109/ICMV.2009.63","DOIUrl":"https://doi.org/10.1109/ICMV.2009.63","url":null,"abstract":"This paper proposes a multimodal biometric system through Gaussian Mixture Model (GMM) for face and ear biometrics with belief fusion of the estimated scores characterized by Gabor responses and the proposed fusion is accomplished by Dempster-Shafer (DS) decision theory. Face and ear images are convolved with Gabor wavelet filters to extracts spatially enhanced Gabor facial features and Gabor ear features. Further, GMM is applied to the high-dimensional Gabor face and Gabor ear responses separately for quantitive measurements. Expectation Maximization (EM) algorithm is used to estimate density parameters in GMM. This produces two sets of feature vectors which are then fused using Dempster-Shafer theory. Experiments are conducted on multimodal database containing face and ear images of 400 individuals. It is found that use of Gabor wavelet filters along with GMM and DS theory can provide robust and efficient multimodal fusion strategy.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"20 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":"124429261","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}
A reliable model for human skin is a significant need for a wide range of computer vision applications ranging from face detection, gesture analysis, content-based image retrieval systems, searching and filtering image content on the web, and to various human computer interaction domains. In this paper, a robust neural model for human skin recognition is first presented. Then, a fully automated neural network based system for recognizing naked people in color images is proposed. The proposed system makes use of a fast and precise neural model, called Multi-level Sigmoidal Neural Network (MSNN). Furthermore, the system exploits four different color models in all their possible representations to precisely extract color features from skin regions. Receiver Operating Characteristics (ROC) curve illustrates that the proposed system outperforms other stat-of-the-art schemes of objectionable image recognition in the context of detection rate and false positive rate. Abundance of experimental results are presented including test images and the ROC curve calculated over a test set, which show stimulating performance of the proposed system.
{"title":"A Robust Neural System for Objectionable Image Recognition","authors":"S. Sadek, A. Al-Hamadi, B. Michaelis, Usama Sayed","doi":"10.1109/ICMV.2009.30","DOIUrl":"https://doi.org/10.1109/ICMV.2009.30","url":null,"abstract":"A reliable model for human skin is a significant need for a wide range of computer vision applications ranging from face detection, gesture analysis, content-based image retrieval systems, searching and filtering image content on the web, and to various human computer interaction domains. In this paper, a robust neural model for human skin recognition is first presented. Then, a fully automated neural network based system for recognizing naked people in color images is proposed. The proposed system makes use of a fast and precise neural model, called Multi-level Sigmoidal Neural Network (MSNN). Furthermore, the system exploits four different color models in all their possible representations to precisely extract color features from skin regions. Receiver Operating Characteristics (ROC) curve illustrates that the proposed system outperforms other stat-of-the-art schemes of objectionable image recognition in the context of detection rate and false positive rate. Abundance of experimental results are presented including test images and the ROC curve calculated over a test set, which show stimulating performance of the proposed system.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"13 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":"114873568","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}
U. Farooq, Hafiz Muhammad Atiq, M. Asad, Asim Iqbal, Z. Azmat
With the increasing number of vehicles on the road, it has become difficult to properly control the flow of traffic especially in large cities like Lahore. The proposed system uses a digital camera mounted on a stepper motor to sense the traffic on the road. The decision to open the lane is done after monitoring the traffic load. The heavily loaded side is turned on for a longer time. Thus the system is intelligent because it is not using the fixed time frame. The system is also integrated with GSM, thus the signals can also be controlled with the help of mobile in case of an emergency. MATLAB® programming environment has been used in simulating and developing the system.
{"title":"Design and Development of an Image Processing Based Adaptive Traffic Control System with GSM Interface","authors":"U. Farooq, Hafiz Muhammad Atiq, M. Asad, Asim Iqbal, Z. Azmat","doi":"10.1109/ICMV.2009.65","DOIUrl":"https://doi.org/10.1109/ICMV.2009.65","url":null,"abstract":"With the increasing number of vehicles on the road, it has become difficult to properly control the flow of traffic especially in large cities like Lahore. The proposed system uses a digital camera mounted on a stepper motor to sense the traffic on the road. The decision to open the lane is done after monitoring the traffic load. The heavily loaded side is turned on for a longer time. Thus the system is intelligent because it is not using the fixed time frame. The system is also integrated with GSM, thus the signals can also be controlled with the help of mobile in case of an emergency. MATLAB® programming environment has been used in simulating and developing the system.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"8 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":"129552710","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}
In this paper, we propose a system to recognize alphabet characters (A-Z) and numbers (0-9) in real-time from stereo color image sequences using Hidden Markov Models (HMMs). Additionally, a robust method for hand tracking in a complex environment using Mean-shift analysis in conjunction with 3D depth map is introduced. The depth information solve the overlapping problem between hands and face, which is obtained by passive stereo measuring based on cross correlation and the known calibration data of the cameras. 3D combined features of location, orientation and velocity with respected to Cartesian systems are used. And then, k-means clustering is employed for HMMs codeword. The hand gesture path is recognized using Left-Right Banded topology (LRB) in conjunction Viterbi path. Experimental results demonstrate that, our system can successfully recognize hand gestures with 98.33% recognition rate.
{"title":"Improving Hand Gesture Recognition Using 3D Combined Features","authors":"M. Elmezain, A. Al-Hamadi, B. Michaelis","doi":"10.1109/ICMV.2009.28","DOIUrl":"https://doi.org/10.1109/ICMV.2009.28","url":null,"abstract":"In this paper, we propose a system to recognize alphabet characters (A-Z) and numbers (0-9) in real-time from stereo color image sequences using Hidden Markov Models (HMMs). Additionally, a robust method for hand tracking in a complex environment using Mean-shift analysis in conjunction with 3D depth map is introduced. The depth information solve the overlapping problem between hands and face, which is obtained by passive stereo measuring based on cross correlation and the known calibration data of the cameras. 3D combined features of location, orientation and velocity with respected to Cartesian systems are used. And then, k-means clustering is employed for HMMs codeword. The hand gesture path is recognized using Left-Right Banded topology (LRB) in conjunction Viterbi path. Experimental results demonstrate that, our system can successfully recognize hand gestures with 98.33% recognition rate.","PeriodicalId":315778,"journal":{"name":"2009 Second International Conference on Machine Vision","volume":"49 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":"123016613","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}
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