Shape and spatial color information extraction for image retrieval

2001 ◽  
Author(s):  
Panagiotis Androutsos ◽  
Diana Ferrari ◽  
Allen Ly ◽  
Andrew Persaud ◽  
Dimitrios Androutsos ◽  
...  
Keyword(s):  
Image Retrieval ◽  
Information Extraction ◽  
Color Information

scholarly journals Image Retrieval Using the Intensity Variation Descriptor

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Zhao Wei ◽  
Guang-Hai Liu
Keyword(s):  
Image Retrieval ◽  
Information Extraction ◽  
Lateral Inhibition ◽  
Intensity Variation ◽  
Spatial Layout ◽  
Inhibition Mechanism ◽  
Square Root ◽  
Optimal Direction ◽  
Selective Mechanism ◽  
Better Than

Variations between image pixel characteristics contain a wealth of information. Extraction of such cues can be used to describe image content. In this paper, we propose a novel descriptor, called the intensity variation descriptor (IVD), to represent variations in colour, edges, and intensity and apply it to image retrieval. The highlights of the proposed method are as follows. (1) The IVD combines the advantages of the HSV and RGB colour spaces. (2) It can simulate the lateral inhibition mechanism and orientation-selective mechanism to determine an optimal direction and spatial layout. (3) An extended weighted L1 distance metric is proposed to calculate the similarity of images. It does not require complex operations such as square or square root and leads to good performance. Comparative experiments on two Corel datasets containing 15,000 images show that the proposed method performs better than the SoC-GMM, CPV-THF, and STH methods and provides good matching of texture, colour, and shape.

20Clustered Domain Colors and Bag of Words Algorithm Based Image Retrieval

2013 ◽  
Vol 321-324 ◽  
pp. 956-960 ◽  
Author(s):  
Lei Tang ◽  
Chang Sheng Zhou ◽  
Liang Zhang
Keyword(s):  
Object Recognition ◽  
Image Retrieval ◽  
Search Algorithm ◽  
Recognition Algorithm ◽  
Features Extraction ◽  
Bag Of Words ◽  
Semantic Features ◽  
Color Information ◽  
Visual Words ◽  
Detection And Recognition

Bag of words algorithm is an efficient object recognition algorithm based on semantic features extraction and expression. It learns the virtues of the text-based search algorithm to make images a range of visual words, extract the semantic characters and carry out the detection and recognition of interesting objects. Bag of words algorithm is extracted from gray images and discard s color information of images. We propose in this paper a method of image retrieval based on clustered domain colors and bag of words algorithm. The results of experiments show that this method can improve the precision of retrieval efficiently.

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.

Perceptual Image Retrieval by Adding Color Information to the Shape Context Descriptor

2010 ◽  
Author(s):  
Marcal Rusinol ◽  
Farshad Noorbakhsh ◽  
Dimosthenis Karatzas ◽  
Ernest Valveny ◽  
Josep Llados
Keyword(s):  
Image Retrieval ◽  
Color Information ◽  
Shape Context
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