FDEIR: Content-Based Image Retrieval using Fast Demeanor Ensemble Features
Main Article Content
Abstract
The demand for CBIR-based systems is increasing day-by-day with the increase of its applications. Nowadays, various digital information systems like Medicine, Digital Libraries, Biodiversity information systems, Fingerprint Identification, crime prevention, and many more are in trend, and all these systems need accuracy. Several Automated Systems were earlier developed using features to improve the systems' accuracy, but it introduces complexity and speed. A fast Demeanor Ensemble features-based approach is proposed to cope with this issue, which also deals with accuracy, speeds up the system, and reduces its complexity. Different shape-based features are used to form 3-set composite features, followed by the selection phase where the ALO algorithm is utilized and reduces system complexity. The accuracy of the proposed system is estimated using distance-based matching methods. Correl-1000 dataset is used to analyze the system's performance based on different metrics, and the results show the proposed system's ability.
Downloads
Metrics
Article Details
Licensing
TURCOMAT publishes articles under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This licensing allows for any use of the work, provided the original author(s) and source are credited, thereby facilitating the free exchange and use of research for the advancement of knowledge.
Detailed Licensing Terms
Attribution (BY): Users must give appropriate credit, provide a link to the license, and indicate if changes were made. Users may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.