Performance Comparison of ZS and GH Skeletonization Algorithms
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Abstract:
Skeletonization is a crucial step in many digital image processing applications like medical imaging, pattern recognition, fingerprint classification etc. The skeleton expresses the structural connectivities of the main component of an object and is one pixel in width. Present paper covers the aspects of pixel deletion criteria in the skeletonization algorithms needed to preserve the connectivity, topology, sensitivity of the binary images. Performance of different skeletonization algorithms can be measured in terms of different parameters such as thinning rate, number of connected components, execution time etc. Present paper focuses on thinning rate, number of connected components, execution time on Zhang and Suen algorithm and Guo and Hall algorithm.Keywords:
Skeletonization
Connected component
Connected-component labeling
Component (thermodynamics)
Medial axis
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A modified context based interpolation algorithm, for digital images, is presented.In the proposed algorithm, the unknown pixel value is exploited based upon the characteristic of a neighboring pixel by considering its edge.The edge is obtained by taking differences of two slopes calculated from neighboring pixels, which are in orthogonal direction.The algorithm uses fourth ordered prediction based approach when interpolating new pixel value by giving suitable weights to the neighboring pixels.This method gives better results as compared to some of existing interpolation methods.Comparison has done using Peak Signal to Noise Ratio (PSNR) and Correlation Coefficient method.
Interpolation
Image scaling
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