Authors:
Hasitha Bimsara Ariyaratne
and
Koichi Harada
Affiliation:
Hiroshima University, Japan
Keyword(s):
Content Based Image Retrieval, Dominant Colours, Text Index, Spatial Relationships.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Feature Extraction
;
Features Extraction
;
Image and Video Analysis
;
Image Formation and Preprocessing
;
Informatics in Control, Automation and Robotics
;
Segmentation and Grouping
;
Signal Processing, Sensors, Systems Modeling and Control
;
Spatial Color Indexing
Abstract:
Content Based Image Retrieval (CBIR) is a quickly evolving area in computer vision and image processing due to the ever increasing number of digital images. Therefore efficient indexing is a vital part in image retrieval systems. Since the ultimate goal of any CBIR system is to simulate the Human visual system (HVS), applying some of the fundamental concepts used in HVS for identifying images such as colour, position size and shape could greatly help enhance the accuracy. Therefore, this research proposes a simple yet effective text based indexing scheme that relies on spatial relationships among dominant colours of image segments. A new connected component labelling approach along with an efficient graph based image segmentation algorithm is used for segment identification. The indexing scheme is capable of identifying both complete and partial image matches. Experiments carried out using different sets of images have yielded promising results, validating the concept’s viability fo
r Content Based Image Retrieval.
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