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This paper discusses the problem of object area detection of video frames. The goal is to design a pixel accurate detector for grass, which could be used for object adaptive video enhancement. A boosting neural network is used for creating such a detector. The resulted detector uses both textural features and color features of the frames.
This paper proposes a localization method of Uygur words in video. First, the video color frame image is preprocessed, while the wavelet transformation is applied and texture entropy is calculated using three-stage wavelet in high frequency details. The entropy is regarded as an important parameter to extract texture characteristic of the image. Further segment each image into some sub-domains and...
Detecting vehicles from video sequence is very challenging due to the wide varieties of vehicle appearances and the complexity of the backgrounds. At present, many algorithms in the image recognition have a narrow applicability and a weak real-time. Aiming at this problem, a recognition method which was combined by features extraction using Gabor wavelet and BP neural network algorithm for the classification...
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