Extraction of image parking spaces in intelligent video surveillance systems

• Autorzy: Bohush R. , Yarashevich P. , Ablameyko S. , Kalganova T.

Identyfikatory

DOI

10.22630/MGV.2018.27.1.3

• Języki publikacji: EN

Abstrakty

EN

This paper discusses the algorithmic framework for image parking lot localization and classification for the video intelligent parking system. Perspective transformation, adaptive Otsu’s binarization, mathematical morphology operations, representation of horizontal lines as vectors, creating and filtering vertical lines, and parking space coordinates determination are used for the localization of parking spaces in a video frame. The algorithm for classification of parking spaces is based on the Histogram of Oriented Descriptors (HOG) and the Support Vector Machine (SVM) classifier. Parking lot descriptors are extracted based on HOG. The overall algorithmic framework consists of the following steps: vertical and horizontal gradient calculation for the image of the parking lot, gradient module vector and orientation calculation, power gradient accumulation in accordance with cell orientations, blocking of cells, second norm calculations, and normalization of cell orientation in blocks. The parameters of the descriptor have been optimized experimentally. The results demonstrate the improved classification accuracy over the class of similar algorithms and the proposed framework performs the best among the algorithms proposed earlier to solve the parking recognition problem.

Słowa kluczowe

EN

parking space; localization; histogram of oriented descriptors; classification; support vector machine

• Wydawca: Institute of Information Technology of the Warsaw University of Life Sciences – SGGW
• Czasopismo: Machine Graphics and Vision
• Rocznik: 2018
• Tom: Vol. 27, No. 1/4
• Strony: 47--62
• Opis fizyczny: Bibliogr. 25 poz., fot., schem., tab.

Twórcy

autor

Bohush R.

• Polotsk State University, Polotsk, Belarus

• https://orcid.org/0000-0002-6609-5810

autor

Yarashevich P.

• Polotsk State University, Polotsk, Belarus

autor

Ablameyko S.

• Belarusian State University, Minsk, Belarus

• https://orcid.org/0000-0001-9404-1206

autor

Kalganova T.

• Brunel University, London, UK

• https://orcid.org/0000-0003-4859-7152

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