Edge-based approach to moving object location

1994 ◽  
Author(s):  
Jung Soh ◽  
Byung-Tae Chun ◽  
Min Wang
2018 ◽  
Vol 7 (2) ◽  
pp. 129-136
Author(s):  
Muhammad Khaerul Naim Mursalim

UAV usually is used in military field for reconnaissance, surveillance, and assault. To detect a moving object in real-time like vessel, there are complex processes than to detect the object that does not moving. There are some issues that faced in detection process of moving object in UAV, called constraint uncertainty factor (UCF) such as environment, type of object, illumination, camera of UAV, and motion. One of the practical problems that become concern of researchers in the past few years is motion analysis. Motion of an object in each frame carries a lot of information about the pixels of moving objects which has an important role as the image descriptor. In this paper, we use SUED (Segmentation using edge-based dilation) algorithm to detect vessel. The concept of the SUED algorithm is combining the frame difference and segmentation process to obtain optimal results. This research showed that the SUED method having problem to detect the vessel even though we combine it with sobel operator. using the combination of wavelet and Sobel operator on the detection of edges obtained increasing in the number of DR about 3%, but then FAR also increased from 41.23% to 52.09%.


Author(s):  
E. Davies

A Generalised Approach to the use of Sampling for Rapid Object LocationThis paper has developed a generalised sampling strategy for the rapid location of objects in digital images. In this strategya prioriinformation on the possible locations of objects is used to guide the sampling process, and earlier body-based and edge-based approaches emerge automatically on applying the righta prioriprobability maps. In addition, the limitations of the earlier regular sampling technique have been clarified and eased—with the result that sampling patterns are better matched to the positions of the image boundaries. These methods lead to improved speeds of operation both in the cases where all the objects in an image have to be located and also where the positions of individual objects have to be updated. Finally, the method is interesting in being intrinsically able to perform full binary search tree edge location without the need for explicit programming.


2020 ◽  
Vol 176 ◽  
pp. 1713-1721
Author(s):  
Mikhail Sergeev ◽  
Anton Sentsov ◽  
Vadim Nenashev ◽  
Elena Turnetskaya

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