Flame Detection Using Generic Color Model and Improved Block-Based PCA in Active Infrared Camera

Author(s):  
Qian Zhao ◽  
Fengdong Sun ◽  
Wenhui Li ◽  
Peixun Liu

In this paper, we proposed an all-weather flame detection algorithm which could make full use of active infrared cameras presently installed in many public places for surveillance purposes. Firstly, according to the different spectral imaging results in day and night, we propose a video type classification algorithm (VTCA) via imaging clues. VTCA could help us select different flame visual features in color image and infrared image. Secondly, we use a generic YCbCr-color-space-based chrominance model to extract regions of interest (ROI) of flame. Thirdly, two flame dynamic features are used to verify the candidate ROIs, which are common flame flicker feature and an improved block-based PCA in consecutive frames. The experimental results show that the proposed flame detection model has been successfully applied to various situations, including day and night, indoor and outdoor on our test video datasets, and it gives a better performance compared with other state-of-the-art methods.

2013 ◽  
Vol 393 ◽  
pp. 556-560
Author(s):  
Nurul Fatiha Johan ◽  
Yasir Mohd Mustafah ◽  
Nahrul Khair Alang Md Rashid

Skin color is proved to be very useful technique for human body parts detection. The detection of human body parts using skin color has gained so much attention by many researchers in various applications especially in person tracking, search and rescue. In this paper, we propose a method for detecting human body parts using YCbCr color spaces in color images. The image captured in RGB format will be transformed into YCbCr color space. This color model will be converted to binary image by using color thresholding which contains the candidate human body parts like face and hands. The detection algorithm uses skin color segmentation and morphological operation.


2011 ◽  
Vol 121-126 ◽  
pp. 672-676 ◽  
Author(s):  
Xin Yan Cao ◽  
Hong Fei Liu

Skin color detection is a hot research of computer vision, pattern identification and human-computer interaction. Skin region is one of the most important features to detect the face and hand pictures. For detecting the skin images effectively, a skin color classification technique that employs Bayesian decision with color statistics data has been presented. In this paper, we have provided the description, comparison and evaluation results of popular methods for skin modeling and detection. A Bayesian approach to skin color classification was presented. The statistics of skin color distribution were obtained in YCbCr color space. Using the Bayes decision rule for minimum cot, the amount of false detection and false dismissal could be controlled by adjusting the threshold value. The results showed that this approach could effectively identify skin color pixels and provide good coverage of all human races, and this technique is capable of segmenting the hands and face quite effectively. The algorithm allows the flexibility of incorporating additional techniques to enhance the results.


2012 ◽  
Vol 182-183 ◽  
pp. 1839-1843
Author(s):  
Xian Zhe Luo ◽  
Nan Run Zhou ◽  
Qing Min Zhao ◽  
Jian Hua Wu

Based on the theory that a color image can be decomposed into three primary components and each one can be seen as a gray image, we propose a color image encryption method with multiple-order discrete fractional cosine transform (MODFrCT), which is a kind of encryption with the secrecy of pixel value and pixel position simultaneously. The complex number mode that has a real part and an imaginary one is used in this encryption method to save the transmission channel. Human vision is more sensitive to the Y component than to other two components in YCbCr color space and this color format is used for encrypting the color image. Chaos is introduced to scramble the image phases both in spatial and transformation domains. The numerical simulations demonstrate the validity and efficiency of this scheme and the robustness of the method against occlusion attack is examined.


2013 ◽  
Vol 446-447 ◽  
pp. 976-980
Author(s):  
De Rui Song ◽  
Dao Yan Xu ◽  
Li Li

This paper proposes a novel algorithm of edge detection using LUV color space. Firstly, according to peer group filtering (PGF), a nonlinear algorithm for image smoothing and impulse noise removal in color image is used. Secondly, color image edges in an image are obtained automatically by combining an improved isotropic edge detector and a fast entropy threshold technique. Thirdly, according to color distance between the pixel and its eight neighbor-pixels, color image edges can further be detected. Finally, the experiment demonstrates the outcome of proposed algorithm in color image edge detection.


2015 ◽  
Vol 15 (2) ◽  
pp. 133-140 ◽  
Author(s):  
Roshan Koju ◽  
Shashidhar Ram Joshi

Since there are a number of color spaces, it has always been a big question to choose one for watermarking. The aim of this work is to find out better color space, among the frequently used one, under the same condition. Comparative performance analysis of color image watermarking technique in color channels of RGB, YUV, YCbCrcolor spaces was studied. For this purpose, color channels were watermarked using single level discrete wavelet transform-singular value decomposition (DWT-SVD). PSNR, and SSIM were used to test the imperceptibility of watermarked images. PSNR and NCC were used to measure the similarity of extracted and original watermarks.The maximum recorded PSNR value is 62.372 for R channel of RGB color space with SSIM value equal to 0.9709. Color channels of YCbCr color space were observed to be more robust and transparent as watermark image is best recovered from YCbCr color space with NCC values in the range 0.86 to 0.877 and SSIM values in the range 0.546to 0.554 under various geometric attacks.DOI: http://dx.doi.org/njst.v15i2.12130Nepal Journal of Science and Technology Vol. 15, No.2 (2014) 133-140


Author(s):  
Warit Sirichotedumrong ◽  
Hitoshi Kiya

AbstractA novel grayscale-based block scrambling image encryption scheme is presented not only to enhance security, but also to improve the compression performance for Encryption-then-Compression (EtC) systems with JPEG compression, which are used to securely transmit images through an untrusted channel provider. The proposed scheme enables the use of a smaller block size and a larger number of blocks than the color-based image encryption scheme. Images encrypted using the proposed scheme include less color information due to the use of grayscale images even when the original image has three color channels. These features enhance security against various attacks, such as jigsaw puzzle solver and brute-force attacks. Moreover, generating the grayscale-based images from a full-color image in YCbCr color space allows the use of color sub-sampling operation, which can provide the higher compression performance than the conventional grayscale-based encryption scheme, although the encrypted images have no color information. In an experiment, encrypted images were uploaded to and then downloaded from Twitter and Facebook, and the results demonstrated that the proposed scheme is effective for EtC systems and enhances the compression performance, while maintaining the security against brute-force and jigsaw puzzle solver attacks.


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