Özet:

nd. The evaluation of video image objects is a relatively difficult task. While solving the task of the geometric representation of a surveillance object, the following additional factors should be considered: possible overlapping of objects, similarity of complex elements, similarity of object elements and background, etc. Objective. The development of a method for complicated objects shape evaluation for application in video surveillance systems for estimation of dynamics of an object’s movement, examination of the object’s behavior on a probable execution of unauthorized actions, and for other tasks. Methods. The procedure of the background subtraction is used for identification of a raster shape of the surveillance object. To detect a vector shape of the object contours, the DEI approach is applied. The sorting procedures are used for identification of reference contour points and for forming the smooth curves. Results. The proposed method includes the following stages: color space conversion and normalization, object shape detection, contours detection and analysis, sorting of vector data, forming of smooth contour curve, object area computing. When the contour points number is reduced in 1.5 times, an average error of the proposed method compared with the DEI approach for accuracy rate is 0.75 %, for performance rate it is 8.43 %, for resource consuming rate it is 3.09 %.Conclusions. The proposed method allows to define an array of vector contour points which represent an “approximate” surveillance object of a complicated shape and it minimizes the data volume to be used in further analysis of a motion trajectory and other similar tasks without decreasing the accuracy. In addition, this method enables describing the surveillance object by an equal quantity of contour points that in turn can simplify the task of surveillance objects classification.

Anahtar Kelimeler: