It is worth noting that all fire detection algorithms mentioned a

It is worth noting that all fire detection algorithms mentioned above operate in the spatial domain, analyzing pixel values of each frame of video.Recently the use of IP cameras in video selleck Axitinib surveillance has grown significantly, because video surveillance systems based on IP technology are easy to implement at low Inhibitors,Modulators,Libraries cost due to the use of cabling and wireless Internet infrastructure already present in many companies [12]. Moreover, an IP camera not only captures sequences of images, but also has its own processor, memory and operating system, allowing loaded programs to process the captured information without the need of additional computer equipment. IP cameras can also be connected to form networks, making a video surveillance system more reliable.
Generally the information provided by IP camera is encoded data in several formats, such as Motion-JPEG (MJPEG), H.264, etc. [12].The use of IP technology for fire detection offers several advantages, for example IP-camera networks can detect Inhibitors,Modulators,Libraries fire origin, magnitude and propagation in more accurate manner compared with a single video surveillance system. However to efficiently use the IP technology for fire detection purposes, the smoke detection algorithm must perform directly in the Discrete Cosine Transform (DCT) domain, because decoding (from DCT domain to spatial domain) and possible encoding (from spatial domain to DCT domain) are considerably high time consuming processes. However almost all fire detection algorithms including those proposed in [1�C11] are carried out in the spatial domain, analyzing the value of each pixel or block of pixels.
Therefore any implementation of these algorithms in IP technology requires considerably high extra processing time.This Inhibitors,Modulators,Libraries paper proposes a smoke detection algorithm, which is an extended version of that presented in UCAmI’11 [13]. The proposed algorithm operates directly in DCT Inhibitors,Modulators,Libraries domain and can be implemented in IP camera-based surveillance system. The proposed algorithm detects the presence AV-951 of smoke using several smoke features, such as color, motion and spreading characteristics, which are extracted directly from DCT coefficients to avoid the decoding process. To increase the resolution of video frames without significantly increasing the computational cost, fast inter-transformation of DCT coefficients proposed in [14] and [15] are used. The computer simulation results show the efficiency and high smoke detection rates of the proposed algorithm. The rest of this paper is organized as follows: Section 2 describes the proposed video processing-based smoke detection TKI-258 scheme. The experimental results and discussions are shown in Section 3, following by conclusions in Section 4.2.

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