Помехоустойчивый морфологический алгоритм обнаружения вилочного погрузчика на видео
Background: The problem of video-based detection of the moving forklift truck is explored. It is shown that the detection quality of the state-of-the-art local descriptors (SURF, SIFT, FAST, ORB) is not satisfactory if the resolution is low and the lighting is changed dramatically.
Methods: In this paper we propose to use a simple mathematical morphological algorithm to detect the presence of a cargo on the forklift truck. At first, the movement direction is estimated by the updating motion history image method and the front part of the moving object is obtained. Next, contours are detected and binary morphological operations in front of the moving object are used to estimate simple geometric features of empty forklift.
Results: Our experimental study shows that the best results are achieved if the bounding rectangles of empty forklift contours are used as an object validation rule. Namely, FAR and FRR of empty cargo detection is 7\% and 50\% lower than FAR and FRR of the FAST descriptor. The proposed method is much more resistant to the effect of additive noise. The average frame processing time for our morphological algorithm is 5 ms (compare with 35 ms. of FAST method)
Conclusions: The proposed morphological method is task specific and can be used only for forklift truck detection. Additional detection principles need to be added to adopt algorithm for other moving object detection in noisy environment.