Signal Processing and Information Technology. First International Joint Conference, SPIT 2011 and IPC 2011, Amsterdam, The Netherlands, December 1-2, 2011, Revised Selected Papers

Research Article

The Mapping Algorithm of Triangular Vertex Chain Code from Thinned Binary Image

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  • @INPROCEEDINGS{10.1007/978-3-642-32573-1_17,
        author={Lili Wulandhari and Habibollah Haron and Roselina Sallehuddin},
        title={The Mapping Algorithm of Triangular Vertex Chain Code from Thinned Binary Image},
        proceedings={Signal Processing and Information Technology. First International Joint Conference, SPIT 2011 and IPC 2011, Amsterdam, The Netherlands, December 1-2, 2011, Revised Selected Papers},
        proceedings_a={SPIT \& IPC},
        year={2012},
        month={10},
        keywords={Vertex Chain Code Triangular Cells Thinned Binary Image},
        doi={10.1007/978-3-642-32573-1_17}
    }
    
  • Lili Wulandhari
    Habibollah Haron
    Roselina Sallehuddin
    Year: 2012
    The Mapping Algorithm of Triangular Vertex Chain Code from Thinned Binary Image
    SPIT & IPC
    Springer
    DOI: 10.1007/978-3-642-32573-1_17
Lili Wulandhari1,*, Habibollah Haron1,*, Roselina Sallehuddin1,*
  • 1: Universiti Teknologi Malaysia
*Contact email: lili.wulandhari@gmail.com, habib@utm.my, roselina@utm.my

Abstract

Image representation has always been an important and interesting topic in image processing and pattern recognition. In 1999, Bribiesca introduced a new two dimensional chain code scheme called Vertex Chain Code (VCC). VCC is composed of three regular cells, namely rectangular, triangular, and hexagonal. This paper presents the mapping algorithm that covers one of the VCC cells, the Triangular VCC cell. The mapping algorithm consists of a cell-representation algorithm that represents a thinned binary image into triangular cells, and a transcribing algorithm that transcribes the cells into Vertex Chain Code. The algorithms have been tested and validated by using three thinned binary images: L-block, hexagon and pentagon. The results show that this algorithm is capable of visualizing and transcribing them into VCC; it can also be improved by testing on more thinned binary images.