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Exploring Circular Hough Transforms for Detecting Hand Feature Points in Noisy Images from Ghost-Circle Patterns

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Intelligent Technologies and Applications (INTAP 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1382))

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Abstract

Several applications involve the automatic analysis of hand images such as biometry, digit-ratio measurements, and gesture recognition. A key problem common to these applications is the separation of hands from the background. Color based approaches struggle to detect the boundaries of the hand and the background if these have similar colors. This paper thus describes work-in-progress with a spatial approach for finger feature point detection based on the circular Hough transforms. The main challenge is to interpret finger feature points in the patterns of circles amidst noise. The approach was implemented in java and tested on a set of images. The results were assessed using manual visual inspection. Such spatial approaches hold potential for more robust and flexible hand related image analysis application. Moreover, these approaches could also give faster algorithms as there is no need for image binarization and threshold optimization.

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Author information

Authors and Affiliations

  1. Faculty of Technology, Art and Design, Oslo Metropolitan University, Oslo, Norway

    Frode Eika Sandnes

  2. Faculty of Technology, Kristiania University College, Oslo, Norway

    Frode Eika Sandnes

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  1. Frode Eika Sandnes
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Correspondence to Frode Eika Sandnes .

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Editors and Affiliations

  1. NTNU, Gjøvik, Norway

    Sule Yildirim Yayilgan

  2. The Islamia University of Bahawalpur, Punjab, Pakistan

    Imran Sarwar Bajwa

  3. University of Agder, Kristiansand, Norway

    Filippo Sanfilippo

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Sandnes, F.E. (2021). Exploring Circular Hough Transforms for Detecting Hand Feature Points in Noisy Images from Ghost-Circle Patterns. In: Yildirim Yayilgan, S., Bajwa, I.S., Sanfilippo, F. (eds) Intelligent Technologies and Applications. INTAP 2020. Communications in Computer and Information Science, vol 1382. Springer, Cham. https://doi.org/10.1007/978-3-030-71711-7_2

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  • DOI: https://doi.org/10.1007/978-3-030-71711-7_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-71710-0

  • Online ISBN: 978-3-030-71711-7

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