Earticle

초록

영어

Texture segmentation is the process of partitioning an image into regions with different textures containing similar group of pixels. Texture is an important spatial feature, useful for identifying object or region of interest. In texture analysis the foremost task is to extract texture features, which efficiently embody the information about the textural characteristics of the image. This can be used for the segmentation of different textured images. This paper presents a new approach for color texture segmentation using Haralick’s features extracted from color co-occurrence matrices. The originality of this approach is to select the most discriminating color texture features extracted from the color co-occurrence. Symbolic Object Approach is used for achieving texture segmentation.

목차

Abstract
 1. Introduction
 2. Proposed Methodology
  2.1 Color Conversion
  2.2. Color Co - Occurrence Matrix
  2.3 Feature Extraction
  2.4 Segmentation
  2.5 Segmentation Algorithm Using Similarity Approach
 3. Results Obtained by Similarity Measure
 4. Comparative Analysis
 5. Conclusion
 References

키워드

저자

• Dr. G. Uma Maheswari [ National Engineering College, Kovilpatti, Tamilnadu ]
• Dr. K. Ramar [ Einstein College of Engineering, Tirunelveli, Tamilnadu ]
• Dr. D. Manimegalai [ National Engineering College, Kovilpatti, Tamilnadu ]
• V. Gomathi [ National Engineering College, Kovilpatti, Tamilnadu ]
• G. Gowrision [ Institute of Road and Transport Technology, Erode ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605