An FLIR video surveillance system to avoid bridge-ship collision

In this paper, a forward-looking infrared (FLIR) video surveillance system is presented for collision avoidance of moving ships to bridge piers. An image pre-processing algorithm is proposed to reduce clutter noises by multi-scale fractal analysis, in which the blanket method is used for fractal feature computation. Then, the moving ship detection algorithm is developed from image differentials of the fractal feature in the region of surveillance between regularly interval frames. Experimental results have shown that the approach is feasible and effective. It has achieved real-time and reliable alert to avoid collisions of moving ships to bridge piers

A bridge-ship collision avoidance system based on FLIR image sequences

In this paper, a forward-looking infrared (FLIR) video surveillance system is presented for collision avoidance of moving ships to bridge piers. An image preprocessing algorithm is proposed to reduce clutter background by multi-scale fractal analysis, in which the blanket method is used for fractal feature computation. Then, the moving ship detection algorithm is developed from image differentials of the fractal feature in the region of surveillance between regularly interval frames. When the moving ships are detected in region of surveillance, the device for safety alert is triggered. Experimental results have shown that the approach is feasible and effective. It has achieved real-time and reliable alert to avoid collisions of moving ships to bridge piers.

Integrating features for man-made target tracking from FLIR image sequence using particle filter

A new man-made target tracking algorithm integrating features from (Forward Looking InfraRed) image sequence is presented based on particle filter. Firstly, a multiscale fractal feature is used to enhance targets in FLIR images. Secondly, the gray space feature is defined by Bhattacharyya distance between intensity histograms of the reference target and a sample target from MFF (Multi-scale Fractal Feature) image. Thirdly, the motion feature is obtained by differencing between two MFF images. Fourthly, a fusion coefficient can be automatically obtained by online feature selection method for features integrating based on fuzzy logic. Finally, a particle filtering framework is developed to fulfill the target tracking. Experimental results have shown that the proposed algorithm can accurately track weak or small man-made target in FLIR images with complicated background. The algorithm is effective, robust and satisfied to real time tracking.

Type III secretion homologs are present in Brucella melitensis, B-ovis, and B-suis biovars 1, 2, and 3

Protein sequences from characterized type III secretion (TTS) systems were used as probes in silico to identify several TTS gene homologs in the genome sequence of Brucella suis biovar 1 strain 1330. Four of the genes, named flhB, fliP, fliR, and fliF on the basis of greatest homologies to known flagellar apparatus proteins, were targeted in PCR and hybridization assays to determine their distribution among other Brucella nomen species and biovars. The results indicated that flhB, fliP, fliR and fliF are present in Brucella melitensis, Brucella ovis, and Brucella suis biovars 1, 2 and 3. Similar homologos have been reported previously in Brucella abortus. Using RT-PCR assays, we were unable to detect any expression of these genes. It is not yet known whether the genes are the cryptic remnants of a flagellar system or are actively involved in a process contributing to pathogenicity or previously undetected motility, but they are distributed widely in Brucella and merit further study to determine their role.