Digital image processing and computer vision: an introduction to theory and implementations
Digital image processing and computer vision: an introduction to theory and implementations
Multidimensional co-occurrence matrices for object recognition and matching
Graphical Models and Image Processing
Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Trace Transform and Its Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Affine Invariant Features from the Trace Transform
IEEE Transactions on Pattern Analysis and Machine Intelligence
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In this paper, we present methodology for recognising textures from irregularly sampled data. We use features constructed from the trace transform, which represents images with functional values along tracing lines rather than brightness values at sampling points. Once texture classification may be performed using line, as opposed to point representations, there is no problem about using irregularly sampled data. The analysis is performed using tracing lines identified by the Hough transform. The results obtained are compared with the results obtained by performing texture classification using samples on the conventional regular grid.