79,800 research outputs found
Writer Identification Using Inexpensive Signal Processing Techniques
We propose to use novel and classical audio and text signal-processing and
otherwise techniques for "inexpensive" fast writer identification tasks of
scanned hand-written documents "visually". The "inexpensive" refers to the
efficiency of the identification process in terms of CPU cycles while
preserving decent accuracy for preliminary identification. This is a
comparative study of multiple algorithm combinations in a pattern recognition
pipeline implemented in Java around an open-source Modular Audio Recognition
Framework (MARF) that can do a lot more beyond audio. We present our
preliminary experimental findings in such an identification task. We simulate
"visual" identification by "looking" at the hand-written document as a whole
rather than trying to extract fine-grained features out of it prior
classification.Comment: 9 pages; 1 figure; presented at CISSE'09 at
http://conference.cisse2009.org/proceedings.aspx ; includes the the
application source code; based on MARF described in arXiv:0905.123
BLADE: Filter Learning for General Purpose Computational Photography
The Rapid and Accurate Image Super Resolution (RAISR) method of Romano,
Isidoro, and Milanfar is a computationally efficient image upscaling method
using a trained set of filters. We describe a generalization of RAISR, which we
name Best Linear Adaptive Enhancement (BLADE). This approach is a trainable
edge-adaptive filtering framework that is general, simple, computationally
efficient, and useful for a wide range of problems in computational
photography. We show applications to operations which may appear in a camera
pipeline including denoising, demosaicing, and stylization
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