Now showing items 1-6 of 6

  • Thumbnail

    A lossless image compression algorithm using predictive coding based on quantized colors 

    Fuangfar Pensiri; Surapong Auwatanamongkol, advisor (National Institute of Development Administration, 2011)

    Predictive coding has proven to be effective for lossless image compression. The predictive coding estimates true color of a pixel based on the true colors of its neighboring pixels. To enhance the accuracy of the estimation, we propose a new and simple predictive coding algorithm that uses the quantized colors of neighboring pixels to estimate the true color of a pixel. The estimation is based on the majority of quantized colors of the three neighboring pixels. Experiments, over a set of true color 24-bit images whose colors of pixels are quantized ...
  • Thumbnail

    Grid-based supervised clustering algorithm using greedy and gradient descent methods to build clusters 

    Pornpimol Bungkomkhun; Surapong Auwatanamongkol, advisor (National Institute of Development Administration, 2012)

    Clustering analysis is one of the primary methods of data mining tasks with the objective to understand the natural grouping (or structure) of data objects in a dataset. The clustering tasks aim to segment the entire data set into relatively homogenous subgroups or clusters where the similarities of the data objects within clusters are maximized and the similarities of data objects belonging to different clusters are minimized. For supervised clustering, not only attribute variables of data objects but also the class variable of data objects take ...
  • Thumbnail

    Local feature representations for facial expression recognition based on differences of gray color values of neighboring pixels 

    Mohammad Shahidul Islam; Surapong Auwatanamongkol, advisor (National Institute of Development Administration, 2013)
  • Thumbnail

    On approximating K-Most probable explanations of Bayesian networks using genetic algorithms 

    Nalerk Sriwachirawat; Surapong Auwatanamongkol, advisor (National Institute of Development Administration, 2006)
  • Thumbnail

    Supervised growing neural gas algorithm in clustering analysis 

    Apirak Jirayusakul; Surapong Auwatanamongkol, advisor (National Institute of Development Administration, 2007)
  • Thumbnail

    Texture classification using an invariant texture representation and a tree matching kernel 

    Somkid Soottitantawat; Surapong Auwatanamongkol, advisor (National Institute of Development Administration, 2010)

    The real world is rich in many textures, which can be regarded as the visual appearance of surfaces. They may be perceived as being smooth or rough, coarse or fine, homogeneous or non-homogeneous, etc. Moreover, textures within real images vary in scale, rotation and illumination. Several researchers have proposed texture analysis methods to describe textures in many applications, such as computer vision, pattern recognition, image retrieval, scene image analysis, and so on. Although the analysis of texture properties has attracted the ...