Abstract：An approach for detection and classification of objects based on Gabor features and enhanced fisher discriminant model (EFM) is presented in this paper. Decomposed by Gabor filters, the dimensions of Gabor features of object images and models are very large. Principal component analysis (PCA) is used to extract the master components and reduce dimensions of Gabor features. Whether there are vehicle objects or not is primarily justified by the magnitude of the Gabor features. If candidate object is detected, EFM is carried out to compare its features to those of models to determine which one it belongs to-vehicles or back ground. The experiments prove the proposed arithmetic can get good results while reducing the feature dimensions. Furthermore, arithmetics for determining vehicle's number and positions are also discussed. And the experimental results also validate their feasibility.
何毅，杨新. 基于Gabor特征和增强Fisher模型的目标检测和识别[J]. 模式识别与人工智能, 2006, 19(4): 455-461.
HE Yi, YANG Xin. Objects Detection and Classification Based onGabor Features and Enhanced Fisher Discriminant Model. , 2006, 19(4): 455-461.
[1] Gabor D. Theory of Communication. Journal of the Institute of Electrical Engineers, 1949, 93(26): 429-457 [2] Daugman J G. Uncertainty Relation for Resolution in Space, Spatial Frequency and Orientation Optimized by Two-Dimensional Visual Cortical Filter. Journal of Optical Society of America, 1985, 2(7): 1160-1169 [3] Daugman J G. Complete Discrete 2-D Gabor Transforms by Neural Networks for Image Analysis and Compression. IEEE Trans on Acoustics Speech and Signal Processing, 1988, 36(7): 1169-1179 [4] Liu C J, Harry W. Robust Coding Schemes for Indexing and Retrieval from Large Face Databases. IEEE Trans on Image Processing, 2000, 9(1): 132-137 [5] Bhanu B. Automatic Target Recognition: State-of-the-Art Survey. IEEE Trans on Aerospace Electronic Systems, 1986, 22(4): 364-379 [6] Wu X, Bhanu B. Gabor Wavelet Representation for 3-D Object Recognition. IEEE Trans on Image Processing, 1997, 6(1): 47-64 [7] Braithwaite R N, Bhanu B. Hierarchical Gabor Filters for Object Detection in Infrared Image. In: Proc of the IEEE Conference on Computer Vision and Pattern Recognition. Seattle, USA, 1994, 628-631 [8] Casasent D, Smokelin J S. Real, Imaginary and Clutter Gabor Filter Fusion for Detection with Reduced False Alarms. Optical Engineering, 1994, 33(7): 2255-2263 [9] Liu C J, Harry W. Gabor Feature Based Classification Using the Enhanced Fisher Linear Discriminant Model for Face Recognition. IEEE Trans on Image Processing, 2002, 11(4): 467-476 [10]Kanungo T, Mount D M, et al. An Efficient k-Means Clustering Algorithm: Analysis and Implementation. IEEE Trans on Pattern Analysis and Machine Intelligence, 2002, 24(7): 881-892
2006, Vol. 19 
