文章基本信息

标题：Color Texture Segmentation using Binary Tree Cluster Quantization Technique
本地全文：下载
作者：Harshvardhan ; Shabnam Sangwan ; Surya Kiran 等
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：6
DOI：10.15680/ijircce.2015.0306109
出版社：S&S Publications
摘要：Both ray tracing and point-based representations provide means to efficiently display very complex 3Dmodels. Computational efficiency has been the main focus of previous work on ray tracing point-sampled surfaces. Forvery complex models efficient storage in the form of compression becomes necessary in order to avoid costly diskaccess. However, as ray tracing requires neighbourhood queries, existing compression schemes cannot be appliedbecause of their sequential nature. This paper introduces a novel acceleration structure called the Quantized kd-tree,which offers both efficient traversal and storage. The gist of our new representation lies in quantizing the kd-treesplitting plane coordinates. We show that the Quantized kd-tree reduces the memory footprint up to 18 times, notcompromising performance. Moreover, the technique can also be employed to provide LOD (Level-Of-Detail) toreduce aliasing problems, with little additional storage cost.In color image processing, color pixels are traditionally treated as geometric vectors in a Euclidean color space.Typically, the three RGB color directions become the basis vectors of the color space. The quaternion representation ofthe color which considers a color pixel as a point in the 3D cube is used in the proposed system, since the quaternionalgebra provides a very natural way to handle homogeneous coordinates.
关键词：Quantized kd-tree; color pixel; RGB Color.