


Registros recuperados: 27  

 

 

 


Arto Kaarna. 
In this section we have collected experiences when different spectral images were compressed in a lossy manner with various methods described in the previous sections. The following abbreviations are used: • CLW: wavelet transform in the spectral reduction followed by clustering, • CLP: PCA in the spectral reduction followed by clustering, • WT3M: the threedimensional wavelet transform, ChuiLian multiwavelets (Chui & Lian, 1996), • WT3H: the threedimensional wavelet transform, Haar wavelet, • SPP: PCA in the spectral reduction and SPIHT (Said & Pearlman, 1996) in the spatial dimensions, • JP2KP: PCA in the spectral reduction and JPEG2000 (Taubman & Marcellin, 2002) in the spatial dimensions, • JPGP: PCA in the spectral reduction and... 
Tipo: 14 
Palavraschave: Vision Systems: Segmentation and Pattern Recognition. 
Ano: 2007 
URL: http://www.intechopen.com/articles/show/title/compression_of_spectral_images 
 

 

 

 

 

 

 

 

 

 


Wei Zhang; Q.M. Jonathan Wu; Xiangzhong Fang. 
In this chapter, we have provided a brief overview of the works about moving cast shadow detection. The stateoftheart methods have been categories into color model, textural model, and geometric model according to the information and model utilized, which have been disscussed systemically. Furthermore, all kinds of statistical models have been employed to tackle the problem, which are also analyzed in detail. From the results, we can see that different method is fit for different situation and it is very hard to get a method in common use. Therefore, the future work may be the fusion of different information by statistical model to realize robust shadow detection. 
Tipo: 3 
Palavraschave: Vision Systems: Segmentation and Pattern Recognition. 
Ano: 2007 
URL: http://www.intechopen.com/articles/show/title/moving_cast_shadow_detection 
 


Michal Haindl; Pavel Zid. 
We proposed novel fast and accurate range segmentation method based on the combination of range & intensity profile modelling and curvebased region growing. A range profile is modelled using an adaptive simultaneous regression model. The recursive adaptive predictor uses spatial correlation from neighbouring data what results in improved robustness of the algorithm over rigid schemes, which are affected with outliers often present at the boundary of distinct shapes. A parallel implementation of the algorithm is straightforward, every image row and column can be processed independently by its dedicated processor. The region growing step is based on the cubic spline curve model. The algorithm performance is demonstrated on the set of test range images... 
Tipo: 2 
Palavraschave: Vision Systems: Segmentation and Pattern Recognition. 
Ano: 2007 
URL: http://www.intechopen.com/articles/show/title/multimodal_range_image_segmentation 
 


Celine Mancas Thillou; Bernard Gosselin. 
This last section aims at concluding this chapter by summing up main steps in the first part to highlight important points according to us to realize an efficient and versatile NS text understanding and the second parts emphasizes interesting work prolongations in other image processing fields and the focus to give in next years. Our SMC algorithm has been proposed based on a multihypothesis text extraction by selecting either the right clustering metric or the dual information between colour and illumination, using logGabor filters. Several points have been detailed such as the superiority of metrics over colour spaces in a clustering framework inside a general NS context. Anglebased similarities have overcome any other colour spaces to handle complex... 
Tipo: 16 
Palavraschave: Vision Systems: Segmentation and Pattern Recognition. 
Ano: 2007 
URL: http://www.intechopen.com/articles/show/title/natural_scene_text_understanding 
 

 


PengYeng Yin. 
In this chapter, we investigate the polygonal approximation problem which is fundamental to many image analysis tasks. Traditional problemspecific heuristics are not suitable to be applied alone because the quality of the obtained result depends on the initial setting of the algorithms and the properties of the curves. On the other hand, metaheuristic approaches can produce stable approximation quality for various kinds of curves. We have illustrated the implementations based on two newly developed metaheuristics, namely the ACO and the PSO. To circumvent the underlying problem, specific features have been introduced such as the ACO graph representation, PSO genetic operators, penalty functions, and the hybrid strategy. Experimental results on several... 
Tipo: 24 
Palavraschave: Vision Systems: Segmentation and Pattern Recognition. 
Ano: 2007 
URL: http://www.intechopen.com/articles/show/title/polygonal_approximation_of_digital_curves_using_the_stateoftheart_metaheuristics 
 


A. G. Tashlinskii. 
The considered PGAs can be directly used in various applied problems of image processing. The algorithms of this class can be applied to image processing in the conditions of a priori uncertainty, they assume small computational expenses and do not require the preliminary estimation of the parameters of the image to be studied. The estimates formed through them are immune to impulse interference and converge to optimal values under rather weak conditions. At an unknown set of the parameters of geometrical deformations model PGAs enable to estimate shifts of each node of image sample grid. At a given IIGD model the processing of the image samples can be performed in an arbitrary order, for example, in order of scanning with decimation that is determined by... 
Tipo: 25 
Palavraschave: Vision Systems: Segmentation and Pattern Recognition. 
Ano: 2007 
URL: http://www.intechopen.com/articles/show/title/pseudogradient_estimation_of_digital_images_interframe_geometrical_deformations 
 
Registros recuperados: 27  


