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A 2D Texture Image Retrieval Technique based on Texture Energy Filters 基于纹理能量滤波器的二维纹理图像检索技术
International Conference on Imaging Theory and Applications Pub Date : 2016-11-17 DOI: 10.5220/0001820701450151
Motofumi T. Suzuki, Y. Yaginuma, Haruo Kodama
{"title":"A 2D Texture Image Retrieval Technique based on Texture Energy Filters","authors":"Motofumi T. Suzuki, Y. Yaginuma, Haruo Kodama","doi":"10.5220/0001820701450151","DOIUrl":"https://doi.org/10.5220/0001820701450151","url":null,"abstract":"In this paper, a database of texture images is analyzed by the Laws’ texture energy measure technique. The Laws’ technique has been used in a number of fields, such as com puter vision and pattern recognition. Although most applications use Laws’ convolution filters with sizes of 3× 3 and 5× 5 for extracting image features, our experimental system uses extended resolutio ns of filters with sizes of 7×7 and 9×9. The use of multiple resolutions of filters makes it possible to extra c various image features from 2D texture images of a database. In our study, the extracted image features wer e selected based on statistical analysis, and the analysis results were used for determining which resolutio ns f features were dominant to classify texture images. A texture energy computation technique was impleme nted for an experimental texture image retrieval system. Our preliminary experiments showed that the system can classify certain texture images based on texture features, and also it can retrieve texture images re flecting texture pattern similarities.","PeriodicalId":231479,"journal":{"name":"International Conference on Imaging Theory and Applications","volume":"101 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131015644","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
Quasi-bi-quadratic Interpolation for LUT Implementation for LCD TV 液晶电视LUT实现的准双二次插值
International Conference on Imaging Theory and Applications Pub Date : 2016-11-07 DOI: 10.5220/0001807600700073
H. Park, G. Seo, Chulhee Lee
{"title":"Quasi-bi-quadratic Interpolation for LUT Implementation for LCD TV","authors":"H. Park, G. Seo, Chulhee Lee","doi":"10.5220/0001807600700073","DOIUrl":"https://doi.org/10.5220/0001807600700073","url":null,"abstract":"Overdriving schemes are used to improve the response time of LCD (Liquid Crystal Display). Typically they are implemented by using LUT (Look-Up Table) within an image processor. However, the size of LUT is limited by the physical memory size and system cost. In actual implementation of LUT, final overdriving values are obtained using interpolation methods. However, interpolation errors may cause some display artifacts and response time delay. In this paper, we present an improved method for LUT implementation using linear interpolation and piecewise least-square polynomial regression to reduce such errors. The proposed method improves LUT performance with reduced memory requirements.","PeriodicalId":231479,"journal":{"name":"International Conference on Imaging Theory and Applications","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126037682","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
CMB Anisotropies Interpolation
International Conference on Imaging Theory and Applications Pub Date : 2009-07-21 DOI: 10.5220/0001434401550158
S. Zinger, J. Delabrouille, M. Roux, H. Maître
{"title":"CMB Anisotropies Interpolation","authors":"S. Zinger, J. Delabrouille, M. Roux, H. Maître","doi":"10.5220/0001434401550158","DOIUrl":"https://doi.org/10.5220/0001434401550158","url":null,"abstract":"We consider the problem of the interpolation of irregularly spaced spatial data, applied to observation of Cosmic MicroWave Background (CMB) anisotropies.The well-known interpolation methods and kriging are compared to the binning method which serves as a reference approach. We analyse kriging versus binning results for different resolutions and noise Ievel in the original data. Most of the time, kriging outperforms the other methods for producing a regularly gridded, minimum variance CMB inap.","PeriodicalId":231479,"journal":{"name":"International Conference on Imaging Theory and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131271088","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 Review on the Current Segmentation Algorithms for Medical Images 医学图像分割算法研究进展
International Conference on Imaging Theory and Applications Pub Date : 1900-01-01 DOI: 10.5220/0001793501350140
Zhen Ma, J. Tavares, R. Jorge
{"title":"A Review on the Current Segmentation Algorithms for Medical Images","authors":"Zhen Ma, J. Tavares, R. Jorge","doi":"10.5220/0001793501350140","DOIUrl":"https://doi.org/10.5220/0001793501350140","url":null,"abstract":"This paper makes a review on the current segmentation algorithms used for medical images. Algorithms are divided into three categories according to their main ideas: the ones based on threshold, the ones based on pattern recognition techniques and the ones based on deformable models. The main tendency of each category with their principle ideas, application field, advantages and disadvantages are discussed. For each considered type some typical algorithms are described. Algorithms of the third category are mainly focused because of the intensive investigation on deformable models in the recent years. Possible applications of these algorithms on segmenting organs and tissues contained in the pelvic cavity are also discussed through several preliminary experiments.","PeriodicalId":231479,"journal":{"name":"International Conference on Imaging Theory and Applications","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134232792","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: 140
Incremental Machine Learning Approach for Component-based Recognition 基于组件识别的增量机器学习方法
International Conference on Imaging Theory and Applications Pub Date : 1900-01-01 DOI: 10.5220/0001783100050012
H. E. Osman
{"title":"Incremental Machine Learning Approach for Component-based Recognition","authors":"H. E. Osman","doi":"10.5220/0001783100050012","DOIUrl":"https://doi.org/10.5220/0001783100050012","url":null,"abstract":"This study proposes an on-line machine learning approach for object recognition, where new images are continuously added and the recognition decision is made without delay. Random forest (RF) classifier has been extensively used as a generative model for classification and regression applications. We extend this technique for the task of building incremental component-based detector. First we employ object descriptor model based on bag of covariance matrices, to represent an object region then run our on-line RF learner to select object descriptors and to learn an object classifier. Experiments of the object recognition are provided to verify the effectiveness of the proposed approach. Results demonstrate that the propose model yields in object recognition performance comparable to the benchmark standard RF, AdaBoost, and SVM classifiers.","PeriodicalId":231479,"journal":{"name":"International Conference on Imaging Theory and Applications","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131070374","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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