• Journal of Information Processing Systems
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• v.15 no.1
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• pp.159-168
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• 2019

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 $L{\ast}a{\ast}b{\ast}$ 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.

• Journal of Korea Multimedia Society
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• v.12 no.5
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• pp.633-643
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• 2009

We propose a color transfer method that used color contrast based templates to express the visual difference clearly between objects, while remaining the quality of the input image. Our algorithm employs colors of both the input image and template distributed on the $a^{\ast}b^{\ast}$chrominance plane of CIE $L^{\ast}a^{\ast}b^{\ast}$color space. The templates are made by considering the effect of color contrast and have the shape of either a line or a curve represented color distribution of the basic colors based gradation image. These tempates can be modeled on spline curves. We also generate simply new templates with the different basic colors by moving the control points of that curve. The color transfer method using the templates is done through a regressive analysis and color matching. We maintained color coherence of the input image by transforming similarly the color distribution of an input image to the one of templates.