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Forest fire detection and identification using image processing and SVM
Mubarak Adam Ishag Mahmoud and Honge Ren
Page: 159~168, Vol. 15, No.1, 2019
10.3745/JIPS.01.0038
Keywords: Background Subtraction, CIE L?a?b? Color Space, Forest Fire, SVM, Wavelet
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Accurate forest fires detection algorithms remain a challenging issue, because, some of the objects have the same features with fire, which may result in high false alarms rate. This paper presents a new video-based, image processing forest fires detection method, which consists of four stages. First, a background-subtraction algorithm is applied to detect moving regions. Secondly, candidate fire regions are determined using CIE L?a?b? color space. Thirdly, special wavelet analysis is used to differentiate between actual fire and fire-like objects, because candidate regions may contain moving fire-like objects. Finally, support vector machine is used to classify the region of interest to either real fire or non-fire. The final experimental results verify that the proposed method effectively identifies the forest fires.


Wavelet-based Digital Image Watermarking by using Lorenz Chaotic Signal Localization
Jantana Panyavaraporn and Paramate Horkaew
Page: 169~180, Vol. 15, No.1, 2019
10.3745/JIPS.03.0109
Keywords: Binary Image, Chaotic Signal, QR Code, Watermarking, Wavelet Analysis
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Transmitting visual information over a broadcasting network is not only prone to a copyright violation but also is a forgery. Authenticating such information and protecting its authorship rights call for more advanced data encoding. To this end, electronic watermarking is often adopted to embed inscriptive signature in imaging data. Most existing watermarking methods while focusing on robustness against degradation remain lacking of measurement against security loophole in which the encrypting scheme once discovered may be recreated by an unauthorized party. This could reveal the underlying signature which may potentially be replaced or forged. This paper therefore proposes a novel digital watermarking scheme in temporal-frequency domain. Unlike other typical wavelet based watermarking, the proposed scheme employed the Lorenz chaotic map to specify embedding positions. Effectively making this is not only a formidable method to decrypt but also a stronger will against deterministic attacks. Simulation report herein highlights its strength to withstand spatial and frequent adulterations, e.g., lossy compression, filtering, zooming and noise.