• Journal of Information Processing Systems
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• v.9 no.4
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• pp.621-632
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• 2013

The most important things for a forest fire detection system are the exact extraction of the smoke from image and being able to clearly distinguish the smoke from those with similar qualities, such as clouds and fog. This research presents an intelligent forest fire detection algorithm via image processing by using the Gaussian Mixture model (GMM), which can be applied to detect smoke at the earliest time possible in a forest. GMMs are usually addressed by making the model adaptive so that its parameters can track changing illuminations and by making the model more complex so that it can represent multimodal backgrounds more accurately for smoke plume segmentation in the forest. Also, in this paper, we suggest a way to classify the smoke plumes via a feature extraction using HSL(Hue, Saturation and Lightness or Luminanace) color space analysis.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.15-24
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• 2011

Recently various anatomic researches by using serially sectioned images in VK(Visible Korean) project are in progress. In that sense, it is very important and necessary to represent images which keep information of the original anatomic images. In this regard, there are some studies to get rid of slice patterns in coronal and sagittal images. However, according to the rapid spatial frequency changes, the ringing effect occurred in common. In addition, because of merge with the original images which have splice patterns, those patterns appeared again. Therefore, in this study we found effective color space to apply to FFT(Fast Fourier Transform) and notch filter in getting rid of the slice patterns. To verify this, we used RGB, LAB, CMYK, HSV and HSL color space. Secondly we got rid of and alleviated the ringing effect by improving notch filter. To verify this, we compared proposed method with previous study on the basis of original images by visual method and objective values. These result images are expected to contribute to anatomy research in relation to VK project.