PCA-Based Feature Selection for MRI Image Retrieval System Using Texture Features

2014 ◽  
pp. 109-117 ◽  
Author(s):  
N. Kumaran ◽  
R. Bhavani
Keyword(s):  
Feature Selection ◽  
Image Retrieval ◽  
Retrieval System ◽  
Texture Features ◽  
Image Retrieval System ◽  
Selection For ◽  
Mri Image

Hyperspectral remote sensing image retrieval system using spectral and texture features

2017 ◽  
Vol 56 (16) ◽  
pp. 4785 ◽  
Author(s):  
Jing Zhang ◽  
Wenhao Geng ◽  
Xi Liang ◽  
Jiafeng Li ◽  
Li Zhuo ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Image Retrieval ◽  
Retrieval System ◽  
Texture Features ◽  
Remote Sensing Image ◽  
Hyperspectral Remote Sensing ◽  
Image Retrieval System ◽  
Hyperspectral Remote Sensing Image

Image Recognition Based on Shape and Texture Features

2014 ◽  
Vol 536-537 ◽  
pp. 127-130
Author(s):  
Kun Geng
Keyword(s):  
Feature Extraction ◽  
Image Retrieval ◽  
Retrieval System ◽  
Texture Features ◽  
Morphological Processing ◽  
Content Based Image Retrieval ◽  
Shape Features ◽  
Key Technologies ◽  
Image Retrieval System ◽  
Important Position

Based on the shape of the image retrieval occupy an important position in the content-based image retrieval, and studied architecture, content-based image retrieval system, ie research-based image retrieval key technologies shape features for image noise in addition to the morphological processing; image segmentation; shape-based feature extraction and regional boundaries and description techniques and similarity measure techniques. The results show that the algorithm can effectively identify the characteristics of the image.

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