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Classification of Textures Using Filter Based Local Feature Extraction

Veysel Gokhan Bocekci, Kazim Yildiz, A. Sikora, B. Choi, S. Wang
2016 MATEC Web of Conferences  
In this work local features are used in feature extraction process in image processing for textures. The local binary pattern feature extraction method from textures are introduced.  ...  Filtering is also used during the feature extraction process for getting discriminative features.  ...  For feature extraction process the common method which is LBP used. LBP is local texture feature extraction method and it's commonly used in texture feature extraction process.  ... 
doi:10.1051/matecconf/20167503001 fatcat:4vk6j4zofvga7nq7sp6logask4

BRINT: Binary Rotation Invariant and Noise Tolerant Texture Classification

Li Liu, Yunli Long, Paul W. Fieguth, Songyang Lao, Guoying Zhao
2014 IEEE Transactions on Image Processing  
Index Terms-Texture descriptors, rotation invariance, local binary pattern (LBP), feature extraction, texture analysis.  ...  In this paper, we propose a simple, efficient, yet robust multiresolution approach to texture classification-binary rotation invariant and noise tolerant (BRINT).  ...  The inherent difficulty in extracting suitable features for robust texture classification lies in balancing the three competing goals of discriminativeness, low computational requirements, and a robustness  ... 
doi:10.1109/tip.2014.2325777 pmid:24860030 fatcat:4ngnqti3mferxeoom34ccg64ge

Local binary patterns and wrinkle analysis in combination with multi-class support vector machine for human age classification

Manesh Kokare, Jayant Jagtap
2017 International Journal of Applied Pattern Recognition  
In this paper, the potential of LBP to capture the minute variations in the textures has been exploited to extract an efficient and robust ageing features invariant to illumination and rotation changes  ...  the three classifiers for the task of human age classification using LBP and wrinkle analysis for ageing feature extraction.  ...  features extraction in combination with M-SVM for age classification.  ... 
doi:10.1504/ijapr.2017.10003552 fatcat:ripqvg5l65egzleaw6rmdrt4qi

Local binary patterns and wrinkle analysis in combination with multi-class support vector machine for human age classification

Jayant Jagtap, Manesh Kokare
2017 International Journal of Applied Pattern Recognition  
In this paper, the potential of LBP to capture the minute variations in the textures has been exploited to extract an efficient and robust ageing features invariant to illumination and rotation changes  ...  the three classifiers for the task of human age classification using LBP and wrinkle analysis for ageing feature extraction.  ...  features extraction in combination with M-SVM for age classification.  ... 
doi:10.1504/ijapr.2017.082651 fatcat:tnqkpmf5hjcv5hau5x5qjbb6me

Locally Directional and Extremal Pattern for Texture Classification

Yongsheng Dong, Tianyu Wang, Chunlei Yang, Lintao Zheng, Bin Song, Lin Wang, Mingxin Jin
2019 IEEE Access  
classification rates in different conditions (rotation, illumination, scale variation, viewpoint variation, and noise) with ten typical texture classification methods.  ...  for texture classification.  ...  We extract LDEP on the datasets without noise while test LDEP on the datasets with noise. Fig. 9 shows the classification accuracy of the seven methods on four noise databases with poisson noise.  ... 
doi:10.1109/access.2019.2924985 fatcat:kgsegnbdc5d4tkc26eb3m2q5su

Degradation adaptive texture classification

Michael Gadermayr, Andreas Uhl
2014 2014 IEEE International Conference on Image Processing (ICIP)  
In experiments with several degradations, classifiers and feature extraction methods, we show that our method continuously and significantly enhances the classification accuracies.  ...  Image degradations such as noise, blur and scale-variations are known to significantly affect the classification process of textured images.  ...  On the one hand, feature extraction methods are required to capture image properties, which are significant for texture discrimination.  ... 
doi:10.1109/icip.2014.7025558 dblp:conf/icip/GadermayrU14 fatcat:pvwc2pz2ongolerkhvtecbxwmy

Texture Representation through Overlapped Multi-oriented Tri-scale Local Binary Pattern

Fawad Fawad, Muhammad Jamil Khan, Muhammad Ali Riaz, Humayun Shahid, Mansoor Shaukat Khan, Yasar Amin, Jonathan Loo, Hannu Tenhunen
2019 IEEE Access  
The experimental results validate the superiority of the proposed method in terms of classification accuracy when compared with the state-of-the-art texture descriptors for noisy images.  ...  geometric transformations within an image.  ...  An increasing number of present-day applications require attaining a higher texture classification accuracy.  ... 
doi:10.1109/access.2019.2918004 fatcat:vz6cy2tzwzbzlozbmjczm5rzzi

Median robust extended local binary pattern for texture classification

Li Liu, Paul Fieguth, Matti Pietikainen, Songyang Lao
2015 2015 IEEE International Conference on Image Processing (ICIP)  
To best address these disadvantages, in this paper, we introduce a novel descriptor for texture classification, the median robust extended LBP (MRELBP).  ...  Index Terms-Texture descriptors, rotation invariance, local binary pattern (LBP), feature extraction, texture analysis.  ...  Consequently, most research in texture classification focuses on the feature extraction part and numerous texture feature extraction methods have been developed, with excellent surveys given in [1] -  ... 
doi:10.1109/icip.2015.7351216 dblp:conf/icip/LiuFPL15 fatcat:xogqixgz4vddpkjwfj22wubpra

Median Robust Extended Local Binary Pattern for Texture Classification

Li Liu, Songyang Lao, Paul W. Fieguth, Yulan Guo, Xiaogang Wang, Matti Pietikainen
2016 IEEE Transactions on Image Processing  
To best address these disadvantages, in this paper, we introduce a novel descriptor for texture classification, the median robust extended LBP (MRELBP).  ...  Index Terms-Texture descriptors, rotation invariance, local binary pattern (LBP), feature extraction, texture analysis.  ...  Consequently, most research in texture classification focuses on the feature extraction part and numerous texture feature extraction methods have been developed, with excellent surveys given in [1] -  ... 
doi:10.1109/tip.2016.2522378 pmid:26829791 fatcat:7mdckt5oibcnlfht2crjy6uafu

Noise-Robust Sound-Event Classification System with Texture Analysis

Yongju Choi, Othmane Atif, Jonguk Lee, Daihee Park, Yongwha Chung
2018 Symmetry  
In this study, we propose a noise-robust system for the classification of sound data.  ...  However, sound-event classification tasks have become more difficult and challenging with the increase in noise levels.  ...  Generally, sound-event classification tasks become more difficult with the increase in noise levels. Many traditional methods show weak performance in the presence of ambient noise [6] .  ... 
doi:10.3390/sym10090402 fatcat:efxdx6vjajh2bawbc3elci2qy4

Local binary features for texture classification: Taxonomy and experimental study

Li Liu, Paul Fieguth, Yulan Guo, Xiaogang Wang, Matti Pietikäinen
2017 Pattern Recognition  
We perform a large scale performance evaluation for texture classification, empirically assessing forty texture features including thirty two recent most promising LBP variants and eight non-LBP descriptors  ...  The best overall performance is obtained for the Median Robust Extended Local Binary Pattern (MRELBP) feature.  ...  Khellah [96] proposed DNS and combined it with LBP for texture classification, claiming noise robustness. Wang et al.  ... 
doi:10.1016/j.patcog.2016.08.032 fatcat:qwjg2fa7abgs7m4bpsbw7vspvy

Symmetric mean and directional contour pattern for texture classification

Yongsheng Dong, Boshi Zheng, Hong Liu, Zhiyong Zhang, Zhumu Fu
2021 Electronics Letters  
By concatenating the RSMP and LDCP, a robust and effective texture descriptor (SMDCP) for classification is built.  ...  In this letter, we propose a simple yet effective texture descriptor, symmetric mean and directional contour pattern (SMDCP), for texture classification.  ...  To improve robustness to noise, the binary rotation invariant and noise tolerant (BRINT) was averaged before binarization [9] and the median robust extended LBP (MRELBP) combined median filters with  ... 
doi:10.1049/ell2.12310 fatcat:vmlunlmrq5drdook3ipqmkb3w4

Circular Mean Filtering For Textures Noise Reduction

M. H Shakoor, F. Tajeripour
2015 Iranian Journal of Electrical and Electronic Engineering  
After applying filter to noisy textures some Local Binary Pattern (LBP) variants are used for feature extraction.  ...  The Implementation part for noisy textures of Outex, UIUC and CUReT datasets shows that using proposed filter increases the classification accuracy significantly.  ...  After that it is possible to extract feature from filtered texture by using LBP or any other feature extraction methods.  ... 
doaj:8c3ca773aec94ff6be41c49635379824 fatcat:oysyg3gvkndjnckhxhc3wz3mgm

Robust Similar Image Retrieval Based on Extracted Object Features

Hiroto Nishiki, Shigeo Wada
2017 Journal of Signal Processing  
A local texture feature as well as global contour and color features are extracted from an object image to generate unified robust feature vectors.  ...  High-performance image retrieval was achieved compared with the conventional methods without using combined robust features of extracted objects.  ...  Conclusions In this paper, a noise-robust object image retrieval method was proposed. Robust local texture, global contour and color histogram features were extracted from an object in an image.  ... 
doi:10.2299/jsp.21.203 fatcat:ad74t24hdzcy5cwm6swsgcacma

Color Context Binary Pattern Using Progressive Bit Correction for Image Classification

SONG Tiecheng, FENG Jie, LI Shuang, ZHANG Tianqi
2021 Chinese journal of electronics  
Experiments on four benchmark databases demonstrate the robustness of CCBP for color image classification under very low signal-to-noise ratio levels.  ...  In this paper, we extend NRLBP to deal with color images and propose a robust color image descriptor called Color context binary pattern (CCBP).  ...  designed to improve the noise-robustness.  ... 
doi:10.1049/cje.2021.03.010 fatcat:7edpxhuk6fgjlijytosvczsibm
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