Integration of discrete wavelet transform, DBSCAN, and classifiers for efficient content based image retrieval
Authors:
- Muhammad Junaid Khalid,
- Muhammad Irfan,
- Tariq Ali,
- Muqaddas Gull,
- Umar Draz,
- Adam Glowacz,
- Maciej Sulowicz,
- Arkadiusz Dziechciarz,
- Fahad Salem AlKahtani,
- Shafiq Hussain
Abstract
In the domain of computer vision, the efficient representation of an image feature vector for the retrieval of images remains a significant problem. Extensive research has been undertaken on Content-Based Image Retrieval (CBIR) using various descriptors, and machine learning algorithms with certain descriptors have significantly improved the performance of these systems. In this proposed research, a new scheme for CBIR was implemented to address the semantic gap issue and to form an efficient feature vector. This technique was based on the histogram formation of query and dataset images. The auto-correlogram of the images was computed w.r.t RGB format, followed by a moment’s extraction. To form efficient feature vectors, Discrete Wavelet Transform (DWT) in a multi-resolution framework was applied. A codebook was formed using a density-based clustering approach known as Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The similarity index was computed using the Euclidean distance between the feature vector of the query image and the dataset images. Different classifiers, like Support Vector (SVM), K-Nearest Neighbor (KNN), and Decision Tree, were used for the classification of images. The set experiment was performed on three publicly available datasets, and the performance of the proposed framework was compared with another state of the proposed frameworks which have had a positive performance in terms of accuracy.
- Record ID
- CUTaa5edad3a2bb4aed93c467556865ff59
- Publication categories
- ;
- Author
- Journal series
- Electronics (Switzerland), ISSN , e-ISSN 2079-9292, Bimonthly
- Issue year
- 2020
- Vol
- 9
- No
- 11
- Pages
- [1-15]
- Article number
- 1886
- Other elements of collation
- schem.; tab.; wykr.; Bibliografia (na s.) - 13-15; Bibliografia (liczba pozycji) - 59; Oznaczenie streszczenia - Abstr.; Numeracja w czasopiśmie - Vol. 9, Iss. 11
- Substantive notes
- Section: Computer Science & Engineering
- Keywords in English
- content-based image retrieval (CBIR), discrete wavelet transform (DWT), features extraction, support vector machine (SVM), decision tree, performance evaluation
- DOI
- DOI:10.3390/electronics9111886 Opening in a new tab
- URL
- https://www.mdpi.com/2079-9292/9/11/1886 Opening in a new tab
- Related project
- E-mobilność oraz zrównoważone materiały i technologie. . Project leader at PK: , ,
- Language
- eng (en) English
- License
- Score (nominal)
- 100
- Publication indicators
- Citation count
- 17
- Additional fields
- Indeksowana w: Web of Science, Scopus
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUTaa5edad3a2bb4aed93c467556865ff59/
- URN
urn:pkr-prod:CUTaa5edad3a2bb4aed93c467556865ff59
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.