Comparison Contour Extraction Based on Layered Structure and Fourier Descriptor on Image Retrieval

In this paper, a new content-based image retrieval technique using shape feature is proposed. A shape features extracted by layered structure representation has been implemented. The approach is extract feature shape by measuring the distance between centroid (center) and boundaries of the object that can capture multiple boundaries in the same angle, an object shape that has some points with the same angle.Once an input taking into account, the method will search most related image to the input. The correlation between input and output has been defined by specific role. Firstly the input image has to be converted from RGB image to Grayscale image and then follow by edge detection process. After edge detection process the boundary object will be obtained and then calculate the distance between the center of an object and the boundary of an object and put it in the feature vector and if there is another boundary on the same angle then put it in the different feature vector with a different layer. The experiment result on the plankton dataset shows that the proposed method better than other conventional Fourier descriptor method.

@article{Rahmad2015,
  title     = {Comparison Contour Extraction Based on Layered Structure and Fourier Descriptor on Image Retrieval},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {6},
  number    = {12},
  year      = {2015},
  publisher = {The Science and Information Organization},
  author    = {Cahya Rahmad and Kohei Arai},
  doi       = {10.14569/IJACSA.2015.061210},
  url       = {https://doi.org/10.14569/IJACSA.2015.061210}
}