УДК: 004.932.2, 517.968

Automatic wavelet-based segmentation of a background-and-target frame from an optoelectronic device for detection of dynamic objects in 2D images

Publication in Journal of Optical Technology

For Russian citation (Opticheskii Zhurnal):

Катулев А.Н., Храмичев А.А. Автоматическая вейвлет-сегментация фоноцелевого кадра оптико-электронного прибора при обнаружении динамических объектов на 2D изображении // Оптический журнал. 2016. Т. 83. № 2. С. 30–39.

Katulev A.N., Khramichev A.A. Automatic wavelet-based segmentation of a background-and-target frame from an optoelectronic device for detection of dynamic objects in 2D images [in Russian] // Opticheskii Zhurnal. 2016. V. 83. № 2. P. 30–39.

For citation (Journal of Optical Technology):

A. N. Katulev and A. A. Khramichev, "Automatic wavelet-based segmentation of a background-and-target frame from an optoelectronic device for detection of dynamic objects in 2D images," Journal of Optical Technology. 83(2), 98-105 (2016). https://doi.org/10.1364/JOT.83.000098

Abstract:

We propose an invariant adaptive technique for automated segmentation of a target-and-background frame from an optoelectronic device for detection of dynamic objects in the image. The technique involves performing a wavelet transform on the image such that threshold processing of wavelet coefficients is optimum (in the sense of the Neyman–Pearson principle) based on a very powerful local unbiased test, and does not require any a priori data on the target environment, any reference images of the dynamic objects, or the locations and dimensions of the windows used for object detection. This is implemented solely using the information contained in images recorded by the optoelectronic device. We present an algorithm and results from an assessment of segmentation quality statistics for non-steady-state (and steady-state) images under various operating conditions. The technique described in this paper is found to be highly efficient and can be implemented as a real-time algorithm.

Keywords:

optoelectronic device, image, segmentation, window, non-steady-state background, dynamic object

OCIS codes: 100.0100; 100.2000; 110.3960; 100.2000

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