A fast algorithm based on the grayscale distribution of infrared target and the weighted kernel function was proposed for the moving target detection(MTD) in dynamic scene of image series. This algorithm is used to de...A fast algorithm based on the grayscale distribution of infrared target and the weighted kernel function was proposed for the moving target detection(MTD) in dynamic scene of image series. This algorithm is used to deal with issues like the large computational complexity, the fluctuation of grayscale, and the noise in infrared images. Four characteristic points were selected by analyzing the grayscale distribution in infrared image, of which the series was quickly matched with an affine transformation model. The image was then divided into 32×32 squares and the gray-weighted kernel(GWK) for each square was calculated. At last, the MTD was carried out according to the variation of the four GWKs. The results indicate that the MTD can be achieved in real time using the algorithm with the fluctuations of grayscale and noise can be effectively suppressed. The detection probability is greater than 90% with the false alarm rate lower than 5% when the calculation time is less than 40 ms.展开更多
In the study of motif discovery, especially the transcription factor DNA binding sites discovery, a too long input sequence would return non-informative motifs rather than those biological functional motifs. This pape...In the study of motif discovery, especially the transcription factor DNA binding sites discovery, a too long input sequence would return non-informative motifs rather than those biological functional motifs. This paper gave theoretical analyses and computational experiments to suggest the length limits of the input sequence. When the sequence length exceeds a certain critical point, the probability of discovering the motif decreases sharply. The work not only gave an explanation on the unsatisfying results of the existed motif discovery problems that the input sequence length might be too long and exceed the point, but also provided an estimation of input sequence length we should accept to get more meaningful and reliable results in motif discovery.展开更多
基金Project(61101185)supported by the National Natural Science Foundation of China
文摘A fast algorithm based on the grayscale distribution of infrared target and the weighted kernel function was proposed for the moving target detection(MTD) in dynamic scene of image series. This algorithm is used to deal with issues like the large computational complexity, the fluctuation of grayscale, and the noise in infrared images. Four characteristic points were selected by analyzing the grayscale distribution in infrared image, of which the series was quickly matched with an affine transformation model. The image was then divided into 32×32 squares and the gray-weighted kernel(GWK) for each square was calculated. At last, the MTD was carried out according to the variation of the four GWKs. The results indicate that the MTD can be achieved in real time using the algorithm with the fluctuations of grayscale and noise can be effectively suppressed. The detection probability is greater than 90% with the false alarm rate lower than 5% when the calculation time is less than 40 ms.
文摘In the study of motif discovery, especially the transcription factor DNA binding sites discovery, a too long input sequence would return non-informative motifs rather than those biological functional motifs. This paper gave theoretical analyses and computational experiments to suggest the length limits of the input sequence. When the sequence length exceeds a certain critical point, the probability of discovering the motif decreases sharply. The work not only gave an explanation on the unsatisfying results of the existed motif discovery problems that the input sequence length might be too long and exceed the point, but also provided an estimation of input sequence length we should accept to get more meaningful and reliable results in motif discovery.
