{"title":"Silk Texture Defect Recognition System Using Computer Vision and Artificial Neural Networks","authors":"A. Oonsivilai, Nittaya Meeboon","doi":"10.1109/CISP.2009.5303972","DOIUrl":"https://doi.org/10.1109/CISP.2009.5303972","url":null,"abstract":"Competiveness of textile industries depends on the quality control of production. In order to minimize production cost, effort is directed towards less defectiveness and time spent on production operations. More accuracy in silk texture defect identification should be maintained so as eliminate any abnormality in the silk texture that hinders its acceptability by the consumer. In this paper, silk texture defect identification is achieved by implementing artificial neural network (ANN) technique. Methodology for feature selection that leads to high recognition rates and to simpler classification systems architectures is presented. Keywords-silk texture; computer-vision; accuracy; artifitial neural network I. INTRODUCTION","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"76 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133053698","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}
{"title":"Effective Dynamic Object Detecting for Video-Based Forest Fire Smog Recognition","authors":"Qinjuan Luo, Ning Han, Jiangming Kan, Z. Wang","doi":"10.1109/CISP.2009.5300888","DOIUrl":"https://doi.org/10.1109/CISP.2009.5300888","url":null,"abstract":"This paper presents an improved novel dynamic smoke detecting method for automatic forest fire surveillance with long- distance video. The first part describes the improved dynamic object detecting technique, that is, the finite thresholding processing to each differential frame after multi-frame temporal difference operation to extract the persistent dynamic behavior of forest smoke from serial forest fire frames. The second part deals with the special characteristics of a real fire smoke (persistence, increase, for example) to discriminate the similar natural phenomena effectively. The early fire which is even not easy to find by manpower was detected with the method in some Forest Park. At the same time the rate of false alarm also is kept within 15%.","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133076300","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}
{"title":"New Method to Solve the End Effect of Empirical Mode Decomposition","authors":"Leitao Zhang, Huanguo Chen, Jianmin Li, Wenhua Chen","doi":"10.1109/CISP.2009.5304936","DOIUrl":"https://doi.org/10.1109/CISP.2009.5304936","url":null,"abstract":"1 Fund Project: Project is provided by State Natural Sciences Fund ( 50805132) and Doctor Conferring Points Foundation of Ministry of Education under the grants (200803380001). Abstract—The end sifting method has been proposed to solve the end effect problem of Empirical Mode Decomposition (EMD). During the Intrinsic Mode Function (IMF) sifting process by EMD method, a procedure including end effect judgment and end sifting, which is different from the traditional idea dealing with the problem by dictating or predicting an end point, is added. This method has greatly improved the precision of IMF.","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133076546","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}
{"title":"A Robust Estimation Method of Interferometric Phase Based on Weighted Subspace Fitting","authors":"Sen Zhang, Yansong Xu, Jinsong Tang","doi":"10.1109/CISP.2009.5301542","DOIUrl":"https://doi.org/10.1109/CISP.2009.5301542","url":null,"abstract":"Interferogram estimate method based on the weight subspace fitting is presented through the subspace fitting of measured signal subspace and the subspace spanned by compound steering vectors. The proposed method can improve the performance of interferogram estimate, using the forward-backward average processing method to decorrelate the signals. The processing results from real data of InSAS show that the performance of proposed method is better and robust than the subspace projecting method’s.","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133433346","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}
{"title":"An Effective Error Concealment Method Based on the Scene Change","authors":"Ning Cao, Zhouyu Li","doi":"10.1109/CISP.2009.5304037","DOIUrl":"https://doi.org/10.1109/CISP.2009.5304037","url":null,"abstract":"This paper proposes a novel error concealment method based on the scene change in H.264. An effective scene change detection mechanism is adopted firstly in this method to detect the scene change. Temporal error concealment is chosen when the temporal redundancy is greater than the spatial redundancy. Otherwise, spatial error concealment is chosen. This method improves the original method of error concealment in H.264. The experiment results demonstrate that the visual quality of image and PSNR are significantly improved.","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132692372","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}
{"title":"Captured Human Motion Segmentation Based on Dynamics and Principal Component Analysis","authors":"Shu-xu Jing, Qi Yuan","doi":"10.1109/CISP.2009.5305323","DOIUrl":"https://doi.org/10.1109/CISP.2009.5305323","url":null,"abstract":"This paper proposes an approach for segmenting single actions from continuously captured motion sequences by examining the properties of active limbs. The target motions are related to sporting and dancing. In particular, two types of human sports motions are examined: 1) boxing and 2) hip hop dance. To segment continuous boxing motion sequences into single punches and combo punches, this paper employs the professional knowl- edge of boxing to compensate for the drawbacks of local minima or maxima detection based motion segmentation approaches. To segment continuous Hip-hop dance sequences into single actions, this papers explores a PCA(Principal Component Analysis) based approach by finding the proper start frame and segment length to perform PCA transformation. Experiments proves that the proposed approach works well.","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131407699","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}
{"title":"Dilution of Precision and Clock of Simulated Pseudolites Augmented GPS Signals","authors":"Chang-hui Xu, Jian Wang, Jingxiang Gao, A. Zhang","doi":"10.1109/CISP.2009.5304466","DOIUrl":"https://doi.org/10.1109/CISP.2009.5304466","url":null,"abstract":"To improve insufficiently available satellite and solve the anomaly geometry, normal GPS system and its mentioned drawbacks are simulated. Based on the analysis of anomaly examples, singular value decomposition (SVD) is applied to settle the anomaly and its effect on precision is investigated. Then pseudolites with proper geometry are laid to increase the number of measurements and advance the geometry to compare with the only GPS normal and anomaly system. The results show that added pseudolites not only solve the problem of no or not good navigation and position solution without enough available measurements, but resolve the lower precision and clock bias because of the anomaly geometry to obtain the required dilution of precision and right clock value.","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131883447","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}
{"title":"Performance Analysis of the Eigen-Space Projection Beamformer Based on Operator Approach","authors":"J. Mu, M. Gao, J. Bai","doi":"10.1109/CISP.2009.5303420","DOIUrl":"https://doi.org/10.1109/CISP.2009.5303420","url":null,"abstract":"In this paper, we propose a new approach resulting in an expression for the probability density function (PDF) of the normalized conditioned signal-to-interference-plus-noise ratio for the eigen-space projection beamformer for antenna arrays of arbitrary geometry. The analysis method is based on the first order perturbation expansion of the projection operator. This technique takes advantage of the algebraic simplicity of the perturbation analysis of linear operators. The probability density is derived from the asymptotic properties of the sample covariance matrix estimated from finite samples. It is shown that, unlike the SMI beamformer, the probability density function depends on the interferenceplus-noise covariance matrix when the interference-to-noise ratio is not high enough. Computer simulation shows the correctness of the method.","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115336319","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}
{"title":"Image Segmentation of Drosophila's Compound Eyes via Two-Dimensional OTSU Thresholding on the Basis of AGA","authors":"Hong-gui Deng, Rang-liang Wu, Zheng-rong Lai","doi":"10.1109/CISP.2009.5303728","DOIUrl":"https://doi.org/10.1109/CISP.2009.5303728","url":null,"abstract":"Image segmentation is a key step in the process of realizing automatic diagnosis of the drosophila’s pathologic compound eyes. This article uses the chromatic aberration variable Cr ,extracted from the color images of drosophila’s compound eyes, to establish a two-dimensional histogram, with which and according to the principle of OTSU thresholding segmentation, image segmentation of the drosophila’s compound eyes has been realized. Based on massive computing of the two-dimensional OTSU thresholding, the Adaptive Genetic Algorithm (AGA), including robustness and parallelity, is then used to search for the best non-linear vector of two-dimensional threshold. A number of experiments are made and the application result proves that the two-dimensional OTSU thresholding method proposed in this paper takes a good effect.","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115544110","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}
Zhiqiang Wei, Lirong Han, Miao Yang, Xiaopeng Ji, B. Yin, Jiansong Chu
{"title":"Building Extraction Based on Hue Cluster Analysis in Complex Scene","authors":"Zhiqiang Wei, Lirong Han, Miao Yang, Xiaopeng Ji, B. Yin, Jiansong Chu","doi":"10.1109/CISP.2009.5304709","DOIUrl":"https://doi.org/10.1109/CISP.2009.5304709","url":null,"abstract":"This paper presents an approach to extract building region in an image with complex scene. The algorithm highlights the edge characteristics of the target in image pre-processing step, uses the improved Hough transform line detection algorithm and the line optimization algorithm to keep the effective straight-line segments. Then it clusters the dominant hues of each effective segment's surrounding area, which will be made statistical analysis to group the straight-lines with building hue and keep the building lines with consistent hue. Finally, the building region is gotten in original image by the effective lines. Our experiments on dozens of pictures by this method and two other building extraction methods, demonstrate that this method is not only good for extracting the covered buildings in complex scene images, but also good for locating the buildings submerged in the background accurately. Keywords-building extraction; improved Hough transform; lines optization; hue clustering","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124191391","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}