Universiti Teknologi Malaysia Institutional Repository

Vessels classification

Suriani, Nor Surayani (2006) Vessels classification. Masters thesis, Universiti Teknologi Malaysia.


Official URL: http://dms.library.utm.my:8080/vital/access/manage...


Moment based invariants, in various forms, have been widely used over the years as features for recognition in many areas of image analysis. The proposed work will look at offline ship recognition using ships silhouette images which will include recognition of part of an object for situations in which only part of the object is visible. The model-based classification is design using Image Processing MATLAB Toolbox. The moment invariant techniques apply for features extraction to obtain moment signatures to do classification. The minimum mean distance classifier is used to classify the ships which works based on the minimum distance feature vector. This research study will address some other issue of classification and various conditions of images that might exist in real environment.

Item Type:Thesis (Masters)
Additional Information:Master of Engineering Electrical (Electronics and Telecommunication )) - Universiti Teknologi Malaysia, 2006;
Uncontrolled Keywords:ships silhouette images, vessel, Image Processing MATLAB
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
H Social Sciences > HE Transportation and Communications
Divisions:Electrical Engineering
ID Code:5567
Deposited By: Narimah Nawil
Deposited On:18 Jun 2008 07:06
Last Modified:17 Sep 2018 03:03

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