Shape Based Image Retrieval Using Fused Features

For content-based image retrieval, the shape is one of the most important discriminatory elements. The form captures most of the perceptual information of the observed objects on images in many applications, while colour and texture can often be omitted without affecting the performance of the retri...

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Bibliographic Details
Main Authors: Maria Abro, Shahnawaz Talpur, Nouman Soomro, Nazish Brohi
Format: Article
Language:English
Published: European Alliance for Innovation (EAI) 2019-01-01
Series:EAI Endorsed Transactions on Internet of Things
Subjects:
Online Access:https://eudl.eu/pdf/10.4108/eai.31-10-2018.159916
Description
Summary:For content-based image retrieval, the shape is one of the most important discriminatory elements. The form captures most of the perceptual information of the observed objects on images in many applications, while colour and texture can often be omitted without affecting the performance of the retrieval. Unfortunately, there may be significant changes in shape, such as deformation, scaling, changes in orientation noise, and partial concealment. Accurate shape description remains, therefore, a challenging technical issue. The study performs experimental analysis to identify the problem. The adoption of the MPEG-7 and KIMIA-99 standard has significant importance to simplify the image retrieval process. The Fourier Descriptors, Moment-Based Features, Hierarchical Centroids and Histogram of Oriented Gradients have been applied forextraction of images from datasets. The fusion of features has been done by Discriminant Correlation Analysis and Direct Concatenation of features it has been evident that by fusion of features we obtained approximately 90% accurate and better results.
ISSN:2414-1399