【正文】 hm proposed by [10], the smoke is considered as a type of texture pattern, which is extracted using local binary patterns (LBP) that are monly used as texture classifier. These LBP are then used to train a MNN which determines the presence of smoke. In [11], using the smoke color property defined in [1] and smoke motion detected by optical flow algorithm, a MNN is trained to detect the presence of smoke. 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 surveillance has grown significantly, because video surveillance systems based on IP technology are easy to implement at low cost due to the use of cabling and wireless Inter infrastructure already present in many panies [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 puter equipment. IP cameras can also be connected to form works, making a video surveillance system more reliable. Generally the information provided by IP camera is encoded data in several formats, such as MotionJPEG (MJPEG), , etc. [12]. The use of IP technology for fire detection offers several advantages, for example IPcamera works can detect fire origin, magnitude and propagation in more accurate ma nner pared 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 9 including those proposed in [1–11] 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 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 domain and can be implemented in IP camerabased surveillance system. The proposed algorithm detects the presence 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 putational cost, fast intertransformation of DCT coefficients proposed in [14] and [15] are used. 2. Proposed Video ProcessingBased Smoke Detection Scheme The proposed smoke detection scheme is designed to work efficiently in an IP camerabased system, in which the sequence encoded by the MJPEG codec is available as input data for the smoke detection algorithm. Recently, IP cameras with codec have been developed。 this problem may be solved using other IP cameras located in other positions. The proposed algorithm can be implemented in IP camera works, where each IP camera can transmit its analysis results to a C4 operation center to obtain more reliable information about the fire, such as the origin, magnitude, growth speed and orientation, etc.