Approach to Detecting Forest Fire by Image Processing Captured from IP Cameras
Journal Title: Journal of Biomedical Engineering and Medical Imaging - Year 2017, Vol 4, Issue 5
Abstract
In this paper, the results show an algorithm to detect the presence of smoke and flame using image sequences captured by Internet Protocol (IP) cameras is represented. The important characteristics of smoke such as color, motion and growth properties are employed to detect fire. For the efficient smoke and fire detection in the captured images by the IP camera, a detection algorithm must operate directly in the Discrete Cosine Transform (DCT) domain to reduce computational weigh, avoiding a complete decoding process required for algorithms that operate in spatial domain. In order to assess the possibility and the accuracy of proposed algorithm, the author used the video sequences which are captured by IP camera from control forest fire at different spatial location and levels of fire intensity. Evaluation results illustrated the efficiency of the proposed algorithm in effectively detecting forest fires with accuracy at 97%.
Authors and Affiliations
Tran Quang Bao, Nguyen Thi Hoa
Keywords
Related Articles
- EP ID EP273364
- DOI 10.14738/jbemi. 45.3856
- Views 90
- Downloads 0
Approach to Detecting Forest Fire by Image Processing Captured from IP Cameras
In this paper, the results show an algorithm to detect the presence of smoke and flame using image sequences captured by Internet Protocol (IP) cameras is represented. The important characteristics of smoke such as color...
Pattern Matching Image Retrieval Technique for Medical Image Database
In current scenario Medical Imaging is becoming very popular due to it’s widely use Medical Profession. Now it became very easy to fetch some useful information from a large data repository using some data mining techniq...
Creation of 3D Volume Loss Mask and Mean Performance Analysis on 3d MR Images
Examination of changes in the brain during disease progression using numerical methods is one of the current topics investigated by neuroscience. One of the numerical methods developed for locally or globally analyzing c...
In vivo Tumor Wavelength Band Selection using Hierarchical Clustering and PCA with NIR-Hyperspectral Data
This paper presents a new method of wavelength selection combined with principle component analysis (PCA) and a hierarchal method for hyperspectral data analysis. Hyperspectral data analysis is a combination of imaging a...
Automated Pulmonary Lung Nodule Detection Using an Optimal Manifold Statistical Based Feature Descriptor and SVM Classifier
The pulmonary lung nodule is the most common indicator of lung cancer. An efficient automated pulmonary nodule detection system aids the radiologists to detect the lung abnormalities at an early stage. In this paper, an...