scholarly journals Comparative Study and Optimization of Feature-Extraction Techniques for Content based Image Retrieval

2012 ◽  
Vol 52 (20) ◽  
pp. 35-42 ◽  
Author(s):  
Aman Chadha ◽  
Sushmit Mallik ◽  
Ravdeep Johar
Keyword(s):  
Feature Extraction ◽  
Comparative Study ◽  
Image Retrieval ◽  
Content Based Image Retrieval ◽  
Extraction Techniques

scholarly journals Content Based Image Retrieval using Texture, Color and Shape for Image Analysis

2012 ◽  
Vol 3 (1) ◽  
pp. 149-152 ◽  
Author(s):  
Amanbir Sandhu ◽  
Aarti Kochhar
Keyword(s):  
Image Analysis ◽  
Feature Extraction ◽  
Image Retrieval ◽  
Content Based Image Retrieval ◽  
Extraction Techniques ◽  
Low Level ◽  
The Past ◽  
Single Feature ◽  
Color Texture

Content- Based Image Retrieval(CBIR) or QBIR  is the important  field of research..Content  Based Image retrieval has gained much popularity  in the past Content-based image retrieval (CBIR)[1] system has also helped users to retrieve relevant images based on their contents. It represents low level features like texture ,color and shape .In this paper, we compare the several feature extraction techniques [5]i.e..GLCM ,Histogram and shape properties  over color,  texture and shape The experiments show the similarity between these features and also that the output obtained using this combination of color, texture and shape is better as obtaining output  with a single feature

scholarly journals Content Based Image Retrieval: A Review

2020 ◽  
Vol 9 (10) ◽  
pp. 222-228
Keyword(s):  
Feature Extraction ◽  
Image Retrieval ◽  
Texture Features ◽  
Image Databases ◽  
Image Recovery ◽  
Content Based Image Retrieval ◽  
Science Content ◽  
Extraction Techniques ◽  
Vision Science ◽  
Retrieval Systems

Image recovery was one of the most thrilling and vibrant fields of computer vision science. Content-based image retrieval systems (CBIR) are used to catalog, scan, download and access image databases automatically. Color & texture features are significant properties for content-based image recovery systems. The content-based image retrieval (CBIR) is therefore an attractive source of accurate and quick retrieval. Number of techniques has been established in recent years to improve the performance of CBIR. This paper discusses why CBIR is important nowadays along with the limitations and benefits. Apart from applications, various feature extraction techniques used in CBIR are also discussed.

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