Abstract
Content Based Satellite Image Retrieval system is used for images processing, weather forecasting, climate monitoring, disaster management, forest fire detection etc. In this research forest, the fire retrieval approach is focused on protecting the forests from fire incidents which can generate an impact on natural resources and living organisms. This research proposed forest fire retrieval approach using proposed hybrid feature extraction technique and Hierarchy Weighted-Brownian Motion Monarch Butterfly Optimization Algorithm based feature selection approach. For application basis, both the proposed feature extraction and feature selection approach are implemented in forest fire retrieval system. The performances of the forest fire retrieval approach are analyzed in terms of precision, recall and accuracy. The efficiency of the proposed approach is evaluated by varying the features such as ground temperature, Top of Atmosphere, Land Surface Temperature, water vapour and intensity. The recall of the proposed fire retrieval approach is increased by 1.68%, 0.6%, 0.62%, 0.54% and precision by 0.82%, 0.41%, 0.75%, and 0.37% when compared with active fire detection, Convolutional Neural Network and hybrid intelligent algorithm respectively. The accuracy of the proposed fire retrieval approach is 98.91% better than the existing approaches.
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References
Alzu’bi A, Amira A, Ramzan N (2019) Learning transfer using deep convolutional features for remote sensing image retrieval. IAENG Intl J Comput Sci 46(4):1–8
Ashraf R, Ahmed M, Jabbar S, Khalid S, Ahmad A, Din S, Jeon G (2018) Content based image retrieval by using color descriptor and discrete wavelet transform. J Med Syst 42(3):44
Baig F, Mehmood Z, Rashid M, Javid MA, Rehman A, Saba T, Adnan A (2020) Boosting the performance of the BoVW model using SURF–CoHOG-based sparse features with relevance feedback for CBIR. Iran J Sci Technol Trans Electric Eng 44(1):99–118
Benjamin SG, Radhakrishnan B, Nidhin TG, Padma Suresh L (2016) Extraction of re region from forest fire images using colour rules and texture analysis. Emerging Technol Trends (ICETT), pp. 1-7
Bhatti UA (2022) Local Similarity-Based Spatial–Spectral Fusion Hyperspectral Image Classification With Deep CNN and Gabor Filtering, in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, Art no. 5514215. https://doi.org/10.1109/TGRS.2021.3090410
Bhatti UA, Huang M, Di W, Zhang Y, Mehmood A, Han H (2019) Recommendation system using feature extraction and pattern recognition in clinical care systems. Enter Inform Syst 13(3):329–351. https://doi.org/10.1080/17517575.2018.1557256
Bhutto A, Xu L, Sattar A (2021) Face recognition system with feature fusion for rehabilitation robots in healthcare, 2021 7th International Conference on Computer and Communications (ICCC), pp.917-921
Chen JN, Huang L, Kpalma KC (2018) Saliency-based multi-feature modeling for semantic image retrieval. J Vis Commun Image Represent 50:199–204
Chhabra P, Garg NK, Kumar M (2020) Content-based image retrieval system using ORB and SIFT features. Neural Comput Appl 32(7):2725–2733
Demir B, Bruzzone L (2014) A novel active learning method in relevance feedback for content-based remote sensing image retrieval. IEEE Trans Geosci Remote Sens 53(5):2323–2334
Di Biase V, Laneve G (2018a) Geostationary sensor based forest fire detection and monitoring: an improved version of the SFIDE Algorithm. Remote Sensing
Hanamaraddi, Priyadarshini M (2016) A literature study on image processing for forest fire detection. IJITR 4(1):2695–2700
Giftlin JGC, Jenicka S (2019a) A strategy for content based image retrieval and forest fire detection from remotely sensed images. ICTACT J Soft Comput 10(01):2015–2021
Jenifer Grace Giftlin C, Jenicka S (2019b) A strategy for content based image retrieval and forest fire detection from remotely sensed images. ICTACT J Soft Comput 10(01):2015–2021
Jonas PN, Keuck V, Peterson K, Siegert F (2012) Monitoring and selective logging activities in tropical peat swamp forests. IEEE J Select Top Appl Earth Observ Remote Sens 5(6):1811–1820
Khatami A, Mirghasemi S, Khosravi A, Lim CP, Nahavandi S (2017a) A new PSO-based approach to fire flame detection using K-Medoids clustering. Expert Syst Appl 68:69–80
Kumar SS, Roy DP (2018) Global operational land imager Landsat-8 reflectance-based active fire detection algorithm, Intl J Digit Earth, vol. 11, no. 2
Latif A, Rasheed A, Sajid U, Ahmed J, Ali N, Ratyal NI, Zafar B, Dar SH, Sajid M, Khalil T (2019) Content-based image retrieval and feature extraction: a comprehensive review. Mathematical Problems in Engineering, 2019
Nair LR, Kamalraj Subramaniam, G. K. D. Prasanna Venkatesan,·P. S. Baskar, T. Jayasankar, (2020), Essentiality for bridging the gap between low and semantic level features in image retrieval systems: an overview. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-020-02139-z.
Nurmaini S, Zarkasi A (2015) Simple Pyramid RAM-Based Neural Network Architecture for Localization of Swarm Robots. J Inform Process Syst 11(3):2015
Rao SS, Ikram S, Ramesh P (2021) Deep Learning-Based Image Retrieval System with Clustering on Attention-Based Representations. SN Comput Sci 2(3):1–16
Srivastava D, Wadhvani R, Gyanchandani M (2015) A Review: Color Feature Extraction Methods for Content Based Image Retrieval. IJCEM Intl J Comput Eng Manage 18(3):9–13
Starovoitov V, Makarau A (2008) Multispectral Image Pre-Processing for Interactive Satellite Image Classification, Research Gate, pp. 1-7
Yo-Ping H, Tsun-Wei C, Li-Jen K, Frode-Eika S (2008) Using fuzzy SOM strategy for satellite image retrieval and information mining. J Syst Cybern Inform 6(1):1–6
Zarkasi A, Sutarno S, Ubaya H, Fajar M (2017) Implementation Color Filtering and Harris Corner Method on Pattern Recognition System. Comput Eng Appl J 6(3):139–144
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The Authors thank the management of the Udaya School of Engineering for their continuous support and encouragement throughout this research. Finally, we would like to thank the anonymous reviewers for helping to organize this text.
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Rani, K.V. Content based image retrieval using hybrid feature extraction and HWBMMBO feature selection method. Multimed Tools Appl 82, 47477–47493 (2023). https://doi.org/10.1007/s11042-023-15716-z
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DOI: https://doi.org/10.1007/s11042-023-15716-z
Keywords
- Content Based Satellite Image Retrieval (CBSIR)
- TOA (Top of Atmosphere)
- LST (Land Surface Temperature)
- Convolutional Neural Network (CNN)
- Adjusted Intensity Based Variant of Adaptive Histogram Equalization (AIBVAHE) filter
- Hierarchy Weighted-Brownian Motion Monarch Butterfly Optimization Algorithm (HWBMMBO)