Application of image visual characterization and soft feature selection in content-based image retrieval

2006 ◽  
Author(s):  
Kambiz Jarrah ◽  
Matthew Kyan ◽  
Ivan Lee ◽  
Ling Guan
Keyword(s):  
Feature Selection ◽  
Image Retrieval ◽  
Content Based Image Retrieval

A Hybrid GA-LDA Scheme for Feature Selection in Content-Based Image Retrieval

2018 ◽  
Vol 9 (2) ◽  
pp. 48-71 ◽  
Author(s):  
Khadidja Belattar ◽  
Sihem Mostefai ◽  
Amer Draa
Keyword(s):  
Feature Selection ◽  
Image Retrieval ◽  
Nearest Neighbor ◽  
Skin Lesions ◽  
Processing Technique ◽  
Input Image ◽  
Content Based Image Retrieval ◽  
K Nearest Neighbor ◽  
Feature Selection Problem ◽  
Linear Discriminant

Feature selection is an important pre-processing technique in the pattern recognition domain. This article proposes a hybridization between Genetic Algorithm (GA) and the Linear Discriminant Analysis (LDA) for solving the feature selection problem in Content-Based Image Retrieval (CBIR) applied to dermatological images. In the first step, we preprocess and segment the input image, then we derive color and texture features characterizing healthy skin and the segmented skin lesion. At this stage, a binary GA is used to evolve chromosome subsets whose fitness is evaluated by a Logistic Regression classifier. The optimal identified features are then used to feed LDA for a CBIR system, based on a K-Nearest Neighbor classification. To assess the proposed approach, the authors have opted for a K-fold cross validation method on a database of 1097 images of melanomas and other skin lesions. As a result, the authors obtained a reduced number of features and an improved CBDIR system compared to PCA, LDA and ICA methods.

scholarly journals A Performance Evaluation of Shape Based Image Retrieval Using Heuristic Function

2013 ◽  
Vol 12 (2) ◽  
pp. 3241-3248
Author(s):  
Parmalik Kumar ◽  
Pushpa Tandekar ◽  
Dhirendra Kumar Jha
Keyword(s):  
Neural Network ◽  
Feature Selection ◽  
Image Retrieval ◽  
Ant Colony Optimization ◽  
Optimization Technique ◽  
Ant Colony ◽  
Content Based Image Retrieval ◽  
Research Trend ◽  
Shape Feature ◽  
Heuristic Function

Heuristic function plays an important role in content based image retrieval. The heuristic function used for feature selection and feature optimization for retrieval process. The feature selection process are depends on feature extraction process. The content based image consists of three types of features such as color, texture and shape. The shape feature is very important feature for image retrieval. The extraction of shape feature various authors used different method such ad Gabor filter, wavelet transform function and Fourier descriptor. Now in current research trend MPEG-7 feature descriptor are mostly authors are used. In this paper descried the review of content based image retrieval based on shape based feature and optimization technique such as ANT colony optimization, genetic algorithm and neural network. The empirical evaluation result shows that ANT colony optimization technique is better optimization technique in compared with other such as genetic and neural network.

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