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| Prateek Sarkar, George Nagy, Jiangying Zhou, Daniel Lopresti, "Spatial Sampling of Printed Patterns," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, no. 3, pp. 344-351, March, 1998. | |||
| BibTex | x | ||
| @article{ 10.1109/34.667892, author = {Prateek Sarkar and George Nagy and Jiangying Zhou and Daniel Lopresti}, title = {Spatial Sampling of Printed Patterns}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {20}, number = {3}, issn = {0162-8828}, year = {1998}, pages = {344-351}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.667892}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Pattern Analysis and Machine Intelligence TI - Spatial Sampling of Printed Patterns IS - 3 SN - 0162-8828 SP344 EP351 EPD - 344-351 A1 - Prateek Sarkar, A1 - George Nagy, A1 - Jiangying Zhou, A1 - Daniel Lopresti, PY - 1998 KW - Spatial sampling KW - random phase sampling KW - digitization KW - optical character recognition KW - document defect models KW - scanner models KW - modulo-grid diagram KW - locales. VL - 20 JA - IEEE Transactions on Pattern Analysis and Machine Intelligence ER - | |||
Abstract—The bitmap obtained by scanning a printed pattern depends on the exact location of the scanning grid relative to the pattern. We consider ideal sampling with a regular lattice of delta functions. The displacement of the lattice relative to the pattern is random and obeys a uniform probability density function defined over a unit cell of the lattice. Random-phase sampling affects the edge-pixels of sampled patterns. The resulting number of distinct bitmaps and their relative frequencies can be predicted from a mapping of the original pattern boundary to the unit cell (called a modulo-grid diagram). The theory is supported by both simulated and experimental results. The modulo-grid diagram may be useful in helping to understand the effects of edge-pixel variation on Optical Character Recognition.
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