Abstract: The static and dynamic characteristics of smoke are developed for extracting smoke pixels of an image and effective smoke detection. In static characteristic, a chromaticity-based analysis is employed to extract grayish pixels in the moving region from a monitored area. Then, a circumference-based disorder measurement in dynamic characteristic is developed to obtain the smoke pixels from the grayish pixels. To enhance the reliability of alarming, a fuzzy system is introduced to judge if the smoke will spread out by checking its growth-rate.

Abstract: The static and dynamic characteristics of smoke are developed for extracting smoke pixels of an image and effective smoke detection. In static characteristic, a chromaticity-based analysis is employed to extract grayish pixels in the moving region from a monitored area. Then, a circumference-based disorder measurement in dynamic characteristic is developed to obtain the smoke pixels from the grayish pixels. To enhance the reliability of alarming, a fuzzy system is introduced to judge if the smoke will spread out by checking its growth-rate.

Abstract: A method for enhancing video data includes inputting image data, providing a first threshold, generating a first mean gray level, generating a first minimum gray level, generating a first maximum gray level, generating a second mean gray level, generating a second minimum gray level, and generating a second maximum gray level. According to the first threshold, generate a second threshold, a third mean gray level, and a fourth mean gray level. According to the third mean gray level, the first gray level, and the first minimum gray level, generate a first gain. According to the fourth mean gray level, the second mean gray level, and the second minimum gray level, generate a second gain. Finally, according to the first mean gray level, the first gain, the third mean gray level, the second mean gray level, the second gain, and the fourth mean gray level; generate enhanced image data.

Abstract: A method and system for detecting early fires in a predetermined area includes capturing a plurality of images of the predetermined area during an interval for generating a plurality of difference frames, and detecting a number of pixels that have fire characteristics in each difference frame. If the detection result indicates that the flame of the predetermined area substantially increases during the interval, the method outputs an early fire alarm that can provide more time for firefighting. Thus, both early fire detection and reduction of false fire alarms are achieved.

Abstract: A method and system for detecting early fires in a predetermined area includes capturing a plurality of images of the predetermined area during an interval for generating a plurality of difference frames, and detecting a number of pixels that have fire characteristics in each difference frame. If the detection result indicates that the flame of the predetermined area substantially increases during the interval, the method outputs an early fire alarm that can provide more time for firefighting. Thus, both early fire detection and reduction of false fire alarms are achieved.

Abstract: A method for enhancing video data includes inputting image data, providing a first threshold, generating a first mean gray level, generating a first minimum gray level, generating a first maximum gray level, generating a second mean gray level, generating a second minimum gray level, and generating a second maximum gray level. According to the first threshold, generate a second threshold, a third mean gray level, and a fourth mean gray level. According to the third mean gray level, the first gray level, and the first minimum gray level, generate a first gain. According to the fourth mean gray level, the second mean gray level, and the second minimum gray level, generate a second gain. Finally, according to the first mean gray level, the first gain, the third mean gray level, the second mean gray level, the second gain, and the fourth mean gray level; generate enhanced image data.

Abstract: A motion detection method based on a detecting system is used to detect a moving object and trigger a corresponding event through a set of consecutive frames. The motion detection method includes comparing duration of the event with a first threshold value for determining whether the event is valid, comparing an interval between two successive events for determining whether the latter of the successive events is combined with the first of the events, and comparing size of the moving object with a predetermined rectangle for determining whether the moving object meets a size limitation of the predetermined rectangle.