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A characterization of cylindrical periodic subsurface defects of different sizes by means of pulsed thermography is presented in the paper. To ensure a uniform thermal flux distribution, the test samples were heated in lab conditions using two photographic flashes. Surface temperature was intentionally recorded at an angle to the normal of the sample surface. Recorded temperatures were compared with simulated temperatures and the differences in temperature peak values and temperature peak positions were noted. The thermal image was transformed based on known positions of four noncollinear points, in order to cancel out errors resulting from image recording at an angle. The uniformity of surface heating and the effect of the positions of the defects on the results were tested by means of a simulation model. The positions did not affect defect characterization. It was also found that in spite of nonuniform heating, if the reference points were selected properly, the difference in temperature contrast was negligible.

The problem of Personalized Face Animation is addressed in this paper by proposing the ShowFace streaming structure. This structure is based on most widely accepted industry standards in multimedia presentation like MPEG-4 and SMIL, extending them by defining image transformations required for certain facial movements, and also by providing a higher level Face Modeling Language (FML) for modeling and control purposes. It defines a comprehensive framework for face animation consisting of components for parsing the input script, generating and splitting the audio and video "behaviors", creating the required images and sounds, and eventually displaying or writing the data to files. This component-based design and scripted behavior make the framework suitable for many purposes including web-based applications. Various examples illustrate the efficiency of our method.

This chapter describes image processing methods for document image analysis. The methods are grouped into four categories, namely, image acquisition, image transformation, image segmentation, and feature extraction. In image acquisition, we describe the process of converting a document into its numerical representation, including image coding as a means to reduce the storage requirement. Image transformation addresses image-to-image operations, which comprise a large spectrum of techniques ranging from geometrical correction, filtering and figure-background separation to boundary detection and thinning. In image segmentation, we describe four popular techniques, namely, connected component labeling, X-Y-tree decomposition, run-length smearing, and Hough transform. Finally, a number of feature extraction methods, which constitute the basis of image classification, are presented.