Rotation invariant texture descriptors based on Gaussian Markov random fields for classification-Reference-Cited by-同舟云学术

Rotation invariant texture descriptors based on Gaussian Markov random fields for classification

Published:2016-01 Issue: Volume:69 Page:15-21
ISSN:0167-8655
Container-title:Pattern Recognition Letters
language:en
Short-container-title:Pattern Recognition Letters

Author:

Dharmagunawardhana Chathurika,Mahmoodi Sasan,Bennett Michael,Niranjan Mahesan

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference45 articles.

1. Image description using joint distribution of filter bank responses;Ahonen;Patt. Recog. Lett.,2009

2. Ridge Regression and Inverse Problems;Björkström,2001

3. C.A. Bouman, MAP, EM, MRFs, and all that: a user’s guide to the tools of model based image and signal processing, https://engineering.purdue.edu/~bouman/ece641/previous/fall08/notes/pdf/Book-header.pdf, 2009.

4. Textures: A Photographic Album for Artists and Designers;Brodatz,1996

5. Classification of textures using Gaussian Markov random fields;Chellappa;IEEE Trans. Acoustics Speech Signal Proc.,1985

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Automatic Diagnosis of COPD in Lung CT Images based on Multi-View DCNN;Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods;2021

2. Adaptive volumetric texture segmentation based on Gaussian Markov random fields features;Pattern Recognition Letters;2020-12

3. Rotation invariant features based on three dimensional Gaussian Markov random fields for volumetric texture classification;Computer Vision and Image Understanding;2020-05

4. Importance of Vertices in Complex Networks Applied to Texture Analysis;IEEE Transactions on Cybernetics;2020-02

5. Model Based Texture Features;Texture Feature Extraction Techniques for Image Recognition;2019-10-25