Biological Cybernetics
Singularity Theory and Phantom Edges in Scale Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Detection of Dominant Points on Digital Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition
Function emulation using radial basis function networks
Neural Networks
Locating Perceptually Salient Points on Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Shape Analysis Model with Applications to a Character Recognition System
IEEE Transactions on Pattern Analysis and Machine Intelligence
Perceptual Model of Handwriting Drawing Application to the Handwriting Segmentation Problem
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
A novel criterion for writer enrolment based on a time-normalized signature sample entropy measure
EURASIP Journal on Advances in Signal Processing - Special issue on recent advances in biometric systems: a signal processing perspective
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Teaching humanoids to imitate 'shapes' of movements
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part II
Teaching a humanoid robot to draw `Shapes'
Autonomous Robots
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A handwritten character magically survives serious distortions in size, orientation and even structure, justifying perhaps its Sanskrit name--Aksharam, the undecaying. Several traditional approaches model characters in terms of certain shape features like line crossings, T-junctions etc. But there is no sanctity in the choice of these features--which may be specific to a script--nor is there a limit to their number. We address the general problem of defining the shape of a 2D line diagram, with character as a significant special case. To this end we develop a framework based on a branch of mathematics known as the Catastrophe theory. A small set of 11 shape features is derived systematically from our framework. The 11 features are found in several of world's scripts and may in fact be universal. More complex shapes break down to the above 11 in handwritten scripts. We discuss how our model can be applied to on-line character recognition from pen-based devices.