GA-Based Affine PPM Using Matrix Polar Decomposition(Pattern Discrimination and Classification,<Special Section>Machine Vision Applications)
スポンサーリンク
概要
- 論文の詳細を見る
Point pattern matching (PPM) arises in areas such as pattern recognition, digital video processing and computer vision. In this study, a novel Genetic Algorithm (GA) based method for matching affine-related point sets is described. Most common techniques for solving the PPM problem, consist in determining the correspondence between points localized spatially within two sets and then find the proper transformation parameters, using a set of equations. In this paper, we use this fact that the correspondence and transformation matrices are two unitary polar factors of Grammian matrices. We estimate one of these factors by the GA's population and then evaluate this estimation by computing an error function using another factor. This approach is an easily implemented one and because of using the GA in it, its computational complexity is lower than other known methods. Simulation results on synthetic and real point patterns with varying amount of noise, confirm that the algorithm is very effective.
- 社団法人電子情報通信学会の論文
- 2006-07-01
著者
-
Faez Karim
Electrical Engineering Department Amirkabir University Of Technology
-
Ezoji Mehdi
Amirkabir Univ. Technol. Tehran Irn
-
Mozaffari Saeed
Electrical Engineering Department Amirkabir University Of Technology
-
EZOJI Mehdi
Electrical Engineering Department, Amirkabir University of Technology
-
RASHIDY KANAN
Electrical Engineering Department, Amirkabir University of Technology
-
Rashidy Kanan
Electrical Engineering Department Amirkabir University Of Technology
-
Ezoji Mehdi
Electrical Engineering Department Amirkabir University Of Technology
-
Faez Karim
Electrical Engineering Dep. Amirkabir Univ. Of Technol.
関連論文
- Design of RBF Neural Network Using An Efficient Hybrid Learning Algorithm with Application in Human Face Recognition with Pseudo Zernike Moment
- A New Efficient Stereo Line Segment Matching Algorithm Based on More Effective Usage of the Photometric, Geometric and Structural Information(Stereo and Multiple View Analysis,Machine Vision Applications)
- GA-Based Affine PPM Using Matrix Polar Decomposition(Pattern Discrimination and Classification,Machine Vision Applications)
- Adaptive Script-Independent Text Line Extraction
- Illumination-Robust Face Recognition from a Single Image per Person Using Matrix Polar Decomposition