In recent years, most multibeam echo sounders (MBESs) have been able to collect water column image (WCI) data while performing seabed topography measurements, providing effective data sources for gas-leakage detection. However, there can be systematic (e.g., sidelobe interference) or natural disturbances in the images, which may introduce challenges for automatic detection of gas leaks. In this paper, we design two data-processing schemes to estimate motion velocities based on the Farneback optical flow principle according to types of WCIs, including time-angle and depth-across track images. Moreover, by combining the estimated motion velocities with the amplitudes of the image pixels, several decision thresholds are used to eliminate interferences, such as the seabed, non-gas backscatters in the water column, etc. To verify the effectiveness of the proposed method, we simulated the scenarios of pipeline leakage in a pool and the Songhua Lake, Jilin Province, China, and used a HT300 PA MBES (it was developed by Harbin Engineering University and its operating frequency is 300 kHz) to collect acoustic data in static and dynamic conditions. The results show that the proposed method can automatically detect underwater leaking gases, and both data-processing schemes have similar detection performance.

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This paper presents a monochromic camera lane can approximate normal road structures, it still cannot detection algorithm based on Snake for improving active describe some cases, i.e. an "S" turn. A deformable template security in intelligent vehicle. The algorithm allows the method was proposed by optimizing a likelihood function elimination of several common assumptions: flat road, based on this model. However, this algorithm cannot constant pitch angle or absence of roll angle, which are the guarantee a global optimum and the accuracy, without limitations of many former algorithms. Moreover, compared . . .with the former methods, the snake based lane model is able to requirig hu c ationa mresourcs. describe any arbitrary shape by a set of control points. We use The approach based on morphological filterig has been an improved Hough transform method to wipe off suggested [8] [9]. This technique used the morphological disturbances caused by shadow or edge of other things. Then watershed" transformation to locate the lane edges in the we get the accurate vanishing points using a method of mutual intensity gradient magnitude image, although this technique comparison to desert some bad ones. The method of update has the advantage of not requiring any threshold for the and tracking is also referenced at last. The results of gradient magnitudes, it has the disadvantage ofnot imposing experiments, which have been done in urban road, show that any global constraints on the lane edge shapes. the algorithm is adapted to many road conditions. Even in aIn this paper, we present an algorithm that is able to detect complex driving environment, it also has a good performance. and follow the roads quickly and robustly. In the first step,

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