Rate the Article: Image Clustering using Color Moments, Histogram, Edge and K-means Clustering, IJSR, Call for Papers, Online Journal
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064

Downloads: 138 | Views: 416

Research Paper | Computer Science & Engineering | India | Volume 2 Issue 1, January 2013 | Rating: 6.2 / 10


Image Clustering using Color Moments, Histogram, Edge and K-means Clustering

Annesha Malakar, Joydeep Mukherjee


Abstract: Clustering a large volume of image database is a challenging research work. Image clustering is needed many practical area like Medical Diagnosis, Military. There exist many traditional way to cluster similar data. But the accuracy level is not so high. So in this paper we propose a new multi feature image clustering technique which will help us to classify the large volume data with high accuracy level. Firstly we extract color moments feature from an image, and then we consider histogram analysis and make a summation of each color bin. Finally we used canny edge detection technique. Lastly we combine all features in a matrix and perform clustering algorithm to cluster data.


Keywords: Color moments, Color Histogram, Edge Detection, Clustering


Edition: Volume 2 Issue 1, January 2013,


Pages: 532 - 537



Rate this Article


Select Rating (Lowest: 1, Highest: 10)

5

Your Comments (Only high quality comments will be accepted.)

Characters: 0

Your Full Name:


Your Valid Email Address:


Verification Code will appear in 2 Seconds ... Wait

Top