Image Retrieval based Convolutional Neural Network
DOI:
https://doi.org/10.23851/mjs.v31i4.897Keywords:
CBIR, preprocessing, feature extraction, PCA, MAD, GLCM, FusionAbstract
At the present time, everyone is interested in dealing with images in different fields such as geographic maps, medical images, images obtaining by Camera, microscope, telescope, agricultural field photos, paintings, industrial parts drawings, space photos, etc. Content Based Image Retrieval (CBIR) is an efficient retrieval of relevant images from databases based on features extracted from the image. Follow the proposed system for retrieving images related to a query image from a large set of images, based approach to extract the texture features present in the image using statistical methods (PCA, MAD, GLCM, and Fusion) after pre-processing of images. The proposed system was trained using 1D CNN using a dataset Corel10k which widely used for experimental evaluation of CBIR performance the results of proposed system shows that the highest accuracy is 97.5% using Fusion (PCA, MAD), where the accuracy is 95% using MAD, 90% using PCA. The performance result is acceptable compared to previous work.
Downloads
References
R.MADANA M., and A.RAMA M. R., "CCBIR: A Cloud Based Implementation of Content Based Image Retrieval", E-ISSN:2224-2872 333 Volume 14, 2015.
Anas F. A.,"A COMPARATIVE STUDY OF HUMAN FACES RECOGNITION USING PRINCIPLE COMPONENTS ANALYSIS AND LINEAR DISCRIMINANT ANALYSIS TECHNIQUES", Vol. 20, No.05, ISSN 2520-0917, 2016.
Manisha V., and Balasubramanian R.,"Local neighborhood difference pattern: A new feature descriptor for natural and texture image retrieval," DOI10.1007/s11042-017-4834-3, 2017.
S.Selvam, and S.Thabasu K.,"A New Architecture for Image Retrieval Optimization with HARP Algorithm," Asian Journal of Computer Science and Technology,ISSN: 2249-0701 Vol. 6 No.1, 2017.
Dr.K.Meenakshisundaram, and G.Vijaiprabhu,"AN ENHANCED CENTER SYMMETRIC LOCAL BINARY PATTERN TECHNIQUE FOR IMAGE RETRIEVAL USING EUCLIDEAN DISTANCE", (IJCRCST) ISSN: 2395-5325Volume 3, Special Issue 1,2017.
Prof.S.Govindaraju, and G.P.Ramesh K., "Content Based Image Retrieval Using Hierarchical and Fuzzy C-Means Clustering" (IJCTT) - Volume 44 Issue 2- February 2017.
Umesh D. D., and M. S. Sh., "Face-based Document Image Retrieval System," ICCIDS,2018.
Mamta M., Shrutika M., and Shrusti T.,"Effectiveness of Saas Cloud Model For Retrieving Images From CBIR System", (IOSRJEN) ISSN (e): 2250-3021, ISSN (p): 2278-8719 PP 70-74, 2018.
Sidi A. M., Mohammed A. B., El.Wardani D., Saïd Mahmoudi and Mohammed B. , "Cloud-Based Image Retrieval Using GPU Platforms," doi: 10.3390/computers8020048,2019.
Vo T. H. T.,Nguyen M. H. , Pham B. Q., Nguyen T. S., and Nguyen T.," Adaptive Content-Based Medical Image Retrieval Based On Local Features Extraction In Shearlet Domain", EAI, 2019.
Nitika S., and Sonika J.," A REVIEW ON CONTENT BASED IMAGE RETRIEVAL," ISSN2277-3061Volume15Number14INTERNATIONAL IOURNAL OF COMPUTERS &TECHNOLOGY,2017.
A.Rama, and C.Nalini,"A REVIEW ON VARIOUS IMAGE RETRIEVAL TECHNIQUES AND ITS APPLICATIONS," ISSN: 0975-766XCODEN: IJPTFI, 2016.
Naveena AK, and N.K.Narayanan, "Sub-Block based Color Moments, Wavelet and Edge Histogram for Image Retrieval," Volume 4 Issue 3; IEEE Network, 2017.
Mamta M., Vinayak A. B.,and Krunali V.," Hybrid Wavelet Based CBIR System using Software as a Service (SaaS) Model on public Cloud," Procedia Computer Science 79 -278 - 286,2016.
Mr. Yogen M. L.,and Prof. Sushant J. P., "A novel method for Content Based Image retrieval using Local features and SVM classifier," (IRJET) e-ISSN: 2395-0056 Volume: 04 Issue:0 7, 2017.
Priya R,"Machine Learning with Optimized Features for Enriched Performance of Content Based Image Retrieval,"Shodhganga, 2015.
Shikha K.," An Hybrid Algorithm to Currency Recognition using Digital Image Processing and Feature Extraction," IJAST ,Vol. 27, No. 1,pp. 244-250,2019.
Higham, Nicholas J. Pranesh, and Srikara "SIMULATING LOW PRECISIONFLOATING-POINT ARITHMETIC,"The University of ManchesterManchester, M13 9PL, UK,2019.
Asia M. N.,"Color to Grayscale Image Conversion Based Dimensionality Reduction with Stationary Wavelet Transform," DOI: 10.1109/AIC-MITCSA, 7759946, 2018.
Muthana H. ,"Digital Image Processing,"2017.
Qin X. , Qiang Z., Duo H.,and Jinpei L.," Removal of Salt and Pepper Noise in Corrupted Image Based on Multilevel Weighted Graphs and IGOWA Operator," doi.org/10.1155/7975248 ,2018.
Raniah A. M., Kawther T. S. ,and Haitham S. C.," Feature Extraction Based on Wavelet Transform and Moment Invariants for Medical Image," DOI: doi.org/10.31695/ IJERAT,3315, Volume.4, Issue 8, 2018.
S.C.Ng, "Principal component analysis to reduce dimension on digital image," Procedia Computer Science 113-119, 10.1016/j.procs.06.017,2017.
N.Santhi, K.Annbuselvi, and S. Sivakumar," Performance Analysis of Feature Extraction Techniques: PCA and LDA for Face Recognition ," ISSN (Online) 2394-2320, (IJERCSE) Vol 5, Issue 3, 2018.
Ningthoujam S. D., and K.Hemachandran,"Face Recognition Using Principal Component Analysis," (IJCSIT), Vol. 5 (5), 6491-6496, 2014.
Downloads
Key Dates
Published
Issue
Section
License
Articles accepted for publication in Al-Mustansiriyah Journal of Science (MJS) are protected under the Creative Commons Attribution 4.0 International License (CC BY-NC). Authors of accepted articles are requested to sign a copyright release form prior to their article being published. All authors must agree to the submission, sign copyright release forms, and agree to be included in any correspondence between MJS and the authors before submitting a work to MJS. For personal or educational use, permission is given without charge to print or create digital copies of all or portions of a MJS article. However, copies must not be produced or distributed for monetary gain. It is necessary to respect the copyright of any parts of this work that are not owned by MJS.
How to Cite
