Title : 
Volume data coding based on region segmentation using finite mixture model
         
        
            Author : 
Ichimura, Naoyuki
         
        
            Author_Institution : 
Electrotech. Lab., Tsukuba, Japan
         
        
        
        
        
        
            Abstract : 
A volume data coding method based on the region segmentation is proposed. The volume data is three dimensional, thus a visualization method is needed. To visualize the desired portions in the volume data, region segmentation is indispensable. Hence, the region-oriented coding is suitable for the volume data. The finite mixture model is used to estimate the probability density function of the feature vectors obtained from the volume data. The volume data is segmented using a posteriori probability calculated from this finite mixture model. The information of the segmented regions are represented as follows: (i) the contours of the regions are represented by the chain code in each slice, (ii) the colors of the regions are represented as the coefficients of the polynomial which is used to approximate those colors, and (iii) since the posteriori probabilities can be regarded as the opacities of the voxels, the opacities which are needed to visualize the segmented regions are represented as the estimated parameters of the finite mixture model. Experimental results for CT data are shown
         
        
            Keywords : 
computerised tomography; data visualisation; image coding; image colour analysis; image representation; image segmentation; medical image processing; probability; CT data; chain code; estimated parameters; experimental results; feature vectors; finite mixture model; image color; image representation; opacities; polynomial coefficients; posteriori probabilities; probability density function; region segmentation; region-oriented coding; visualization method; volume data coding; volume rendering; voxels; Color; Computed tomography; Data visualization; Image coding; Image converters; Image segmentation; Image sequences; Polynomials; Probability; Rendering (computer graphics);
         
        
        
        
            Conference_Titel : 
Image Processing, 1996. Proceedings., International Conference on
         
        
            Conference_Location : 
Lausanne
         
        
            Print_ISBN : 
0-7803-3259-8
         
        
        
            DOI : 
10.1109/ICIP.1996.560506