scholarly journals Use of Color Feature Extraction Technique based on Color Distribution and Relevance Feedback for Content based Image Retrieval

2012 ◽  
Vol 52 (17) ◽  
pp. 9-12
Author(s):  
Sandip S.Patil ◽  
Atul V. Dusane
Keyword(s):  
Feature Extraction ◽  
Image Retrieval ◽  
Relevance Feedback ◽  
Content Based Image Retrieval ◽  
Extraction Technique ◽  
Color Feature ◽  
Color Distribution ◽  
Feature Extraction Technique

Sketch Based Image Retrieval by Using Feature Extraction Technique

2016 ◽  
Vol 6 (1) ◽  
pp. 21-24
Author(s):  
Mohammad Hossein Torabi Motlagh Fard ◽  
Nazean Jomhari ◽  
Sri Devi Ravana
Keyword(s):  
Feature Extraction ◽  
Image Retrieval ◽  
Extraction Technique ◽  
Feature Extraction Technique

scholarly journals Using Color and Texture Feature Extraction Technique to Retrieve Image

2019 ◽  
Vol 8 (11S) ◽  
pp. 915-917
Keyword(s):  
Feature Extraction ◽  
Image Retrieval ◽  
Texture Feature ◽  
Color Images ◽  
Color Histogram ◽  
Gray Level ◽  
Texture Feature Extraction ◽  
Color Feature ◽  
Occurrence Matrix ◽  
Feature Extraction Technique

This paper proposes a content image retrieval using the texture and the color feature of the images. Although for extraction of texture feature, the “gray level co-occurrence matrix (GLCM) algorithm” is used and for extracting color feature the color histogram is used. The presented system is tested on the WANG database that contains a thousand color images with ten different classes by the help of three various type of distances

scholarly journals Relevance Feedback berdasarkan Support Vector Machine pada Content Based Image Retrieval

2012 ◽  
Vol 1 (1) ◽  
Author(s):  
Virginia Tulenan
Keyword(s):  
Support Vector Machine ◽  
Feature Extraction ◽  
Image Retrieval ◽  
Relevance Feedback ◽  
Content Based Image Retrieval ◽  
Support Vector ◽  
Relevant Feedback

Content based image retrieval adalah bidang penelitianyang sangat penting saat ini dalam bidang multimedia database.Banyak penelitian yang telah dilakukan dalam dekade terakhiruntuk merancang teknik image retrieval yang efisien dari imagedatabase. Meskipun banyak teknik pengindeksan dan retrievaltelah dikembangkan, namun masih belum terdapat teknikpemisahan ciri (feature extraction), indexing dan retrieval yangbisa diterima secara universal oleh semua orang. Dalam tulisanini, digunakanlah metode relevant feedback berdasarkan supportvector machine (SVM) dan muhalobis distance untuk pengukurankemiripan pada image retrieval.

scholarly journals COLOR FEATURE WITH SPATIAL INFORMATION EXTRACTION METHODS FOR CBIR: A REVIEW

2019 ◽  
Vol 45 (1) ◽  
pp. 15-19
Author(s):  
Sarmad Abdul-samad
Keyword(s):  
Feature Extraction ◽  
Image Retrieval ◽  
Information Extraction ◽  
Spatial Information ◽  
Extraction Methods ◽  
Content Based Image Retrieval ◽  
Visual Features ◽  
Visual Content ◽  
Color Feature ◽  
Color Correlogram

Inn then last two decades the Content Based Image Retrieval (CBIR) considered as one of the topic of interest for theresearchers. It depending one analysis of the image’s visual content which can be done by extracting the color, texture and shapefeatures. Therefore, feature extraction is one of the important steps in CBIR system for representing the image completely. Color featureis the most widely used and more reliable feature among the image visual features. This paper reviews different methods, namely LocalColor Histogram, Color Correlogram, Row sum and Column sum and Colors Coherences Vectors were used to extract colors featurestaking in consideration the spatial information of the image.

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