Wulansari, Dewi and Martiana, Entin and Ramadijanti, Nana (2010) Pengelompokan Gambar Berdasarkan Fitur Warna Dan Tekstur Menggunakan FGKA Clustering (Fast Genetics K-Means Algorithm) Untuk Pencocokan Gambar. EEPIS Final Project.
| PDF - Published Version Download (1086Kb) | Preview |
Abstract
A large collections of digital images are being created. Usually, the only way of searching these collections was by using meta data (like caption or keywords). This way is not effective, impractical, need a big size of database and giving inaccurate result. Recently, it has been developed many ways in image retrieval that use image content (color, shape, and texture) that more recognised with CBIR ( Content Based Images Retrieval). The use of centroid produced from clustered HSV Histogram and Gabor Filter using FGKA, can be used for searching parameter. FGKA is merger of Genetic Algorithm and Kmeans Clustering Algorithm. FGKA is always converge to global optimum. Image Clustering and Matching based on color-texture feature are better than based on color feature only, texture only or using non-clustering method. Keywords: Genetics Algorithm, K-Means Clustering, CBIR, HSV Histogram, Gabor Filter.
Item Type: | Article |
---|---|
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
Depositing User: | Mrs fariny masna |
Date Deposited: | 15 Apr 2011 21:37 |
Last Modified: | 15 Apr 2011 21:37 |
URI: | http://repo.pens.ac.id/id/eprint/608 |
Actions (login required)
View Item |