The use of the Circular Hough Transform for counting coins

• Autorzy: Gomółka Z. , Żesławska E. , Twaróg B. , Paszkiewicz A.
• Języki publikacji: EN

Abstrakty

EN

The paper presents the circular Hough transform in the process of detecting and counting coins. The issues of linear and circular Hough transform are discussed. An algorithm for counting coins in a three-dimensional image using the discrete Hough space is demonstrated. Moreover, the results of the application for detecting and counting coins in a static image and video stream are presented. Observations of histograms for HSV and RGB color palettes, for different camera resolutions and various parameters of image segmentation, edge detection and smoothing filter have been made.

Słowa kluczowe

EN

Hough transform; image detection; segmentation; digital image processing; edge detection

• Wydawca: Wydawnictwo PAK
• Czasopismo: Measurement Automation Monitoring
• Rocznik: 2015
• Tom: Vol. 61, No. 9
• Strony: 434--437
• Opis fizyczny: Bibliogr. 7 poz., fot., rys., wzory

Twórcy

autor

Gomółka Z.

• Faculty of Mathematics and Natural Sciences Department of Computer Engineering, University of Rzeszow, 1 Pigonia St., 35-959 Rzeszów

autor

Żesławska E.

• Faculty of Applied Informatics, Department of Applied Information, University of Information Technology and Management in Rzeszow, 2 Sucharskiego St., 35-225 Rzeszów

autor

Twaróg B.

• Faculty of Mathematics and Natural Sciences Department of Computer Engineering, University of Rzeszow, 1 Pigonia St., 35-959 Rzeszów

autor

Paszkiewicz A.

• Department of Distributed System, Rzeszow University of Technology, 12 Powstańców Warszawy Ave., 35-959 Rzeszów

Bibliografia

• [1] Mike X. Cohen: Analyzing neural time series data. Theory and Practice, Massachusetts Institute of Technology, 2014.
• [2] Scharcanski J.: Signal and Image Processing for Biometrics, Springer–Verlag, 2014.
• [3] Gomółka Z., Twaróg B., Bartman J., Kwiatkowski B.: Improvement of Image Processing by Using Homogeneous Neural Networks with Fractional Derivatives Theorem. AIMS, Discrete and Continuous Dynamical Systems, 2011.
• [4] Chmielewski L.: Specification of the evidence accumulation-based line detection algorithm. In: Computer Recognition Systems. Proc. Int. Conf. Computer Recognition Systems CORES, Advances in Soft Computing series Vol. 30, Springer, 2005.
• [5] Klepacz. M.: Kołowa transformata Hougha w zadaniu zliczania monet. Praca inżynierska, 2012.
• [6] Żorski W.: Metody segmentacji obrazów oparte na transformacie Hougha. Wojskowa Akademia Techniczna. Wydanie I, Warszawa 2000.
• [7] Owen M.: Przetwarzanie sygnałów w praktyce. Wydawnictwo Komunikacji i Łączności, Wydanie I, Warszawa 2009.