SIMPLEGABOR - Simple Gabor Feature Space

Face image with 10 local points marked simple Gabor feature space of 4 orientations and 5 frequencies Face image reconstruction from 10 points

Goals

The goal of this project is to further develop the new feature structure developed by the authors called as "Simple Gabor Feature Space". Simple Gabor feature space is an efficient structure for representing and detecting small and simple image patches. Furthermore, the proposed space has many beneficial properties, such as reconstruction property, natural tolerance to noise and distortions (deformations), illumination invariance, and invariance properties over translation, scale and rotation.

During the project an efficient implementation of the simple Gabor feature space will be considered. The first milestone of the project is a publicly downloadable efficient Matlab toolbox for computing Gabor features. Later, implementation in other environments besides Matlab will be considered, e.g., implementation in C and/or a parallel computing approach will be under scrutiny. The main objective of the project is to compute simple Gabor features (later called as multiresolution Gabor features) as fast as possible and provide functionality for their rapid utilisation in further processing (e.g. classification).

Sub-projects

News

The project has finished. V1.0.0 of the SimpleGabor Matlab ToolBox has been released.

Contact information

Jarmo Ilonen E-Mail WWW Post-graduate researcher
Joni Kämäräinen E-Mail WWW Project leader, research fellow
Heikki Kälviäinen E-Mail WWW Professor

Download

Source code

  1. Simplegabor toolbox for Matlab - Multiresolution Gabor filtering for 2-D signals

Data sets

  1. -

Links to other resources

Documentation

Do not hesitate to to contact authors (e-mail, etc.) in order to retrieve copies or reprints of the following publications.

  1. Articles in international scientific journals with referee practice
    1. Ville Kyrki, Joni-Kristian Kämäräinen, Heikki Kälviäinen, Pattern Recognition Letters, Simple Gabor Feature Space for Invariant Object Recognition, (2004) pp. 311--318, No. 3 Vol. 25
    2. Joni-Kristian Kämäräinen, Ville Kyrki, Heikki Kälviäinen, IEEE Transactions on Image Processing, Invariance Properties of Gabor Filter Based Features - Overview and Applications, (2006) pp. 1088-1099, No. 5 Vol. 15
    3. Jarmo Ilonen, Joni-Kristian Kämäräinen, Pekka Paalanen, Miroslav Hamouz, Josef Kittler, Heikki Kälviäinen, IEEE Transactions on Image Processing, Image feature localization by multiple hypothesis testing of Gabor features, (2008) pp. 311-325, No. 3 Vol. 17
  2. Articles in international compilation works and in international scientific conference proceedings with referee practice
    1. Joni-Kristian Kämäräinen, Jarmo Ilonen, Pekka Paalanen, Miroslav Hamouz, Heikki Kälviäinen, Josef Kittler, Proc. of the 14th Scandinavian Conf. of Image Analysis, Object Evidence Extraction Using Simple Gabor Features and Statistical Ranking, (2005) pp. 119-129,
    2. Jarmo Ilonen, Joni-Kristian Kämäräinen, Proc. of the Int. Joint Conf. on Neural Networks (IJCNN), Object categorization using self-organization over visual appearance, (2006) pp. 4549-4553,
    3. Jarmo Ilonen, Joni-Kristian Kämäräinen, Heikki Kälviäinen, Proc. of the 14th International Conference on Image Analysis and Processing (ICIAP2007), Fast extraction of multi-resolution Gabor features, (2007) pp. 481-486,
  3. Scientific monographs
    1. Joni-Kristian Kämäräinen, Ph.D thesis, Feature Extraction Using Gabor Filters, (2003) pdf (2.47 MB)
    2. Jarmo Ilonen, Ph.D thesis, Supervised local image feature detection, (2007) pdf (10.26 MB)
  4. Other Scientific Publications
    1. Jarmo Ilonen, Joni-Kristian Kämäräinen, Heikki Kälviäinen, Efficient Computation of Gabor Features, (2005) No. 100 pdf (1.06 MB)
    2. Ville Kyrki, Joni-Kristian Kämäräinen, Simple Gabor Feature Space for Invariant Object Recognition, (2003) No. 83