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Scanning Maps and Learning from Defects

September 24, 2013
G. Salim Mohammed
Segmented Map for Study

 The discovery of a particular scanning defect called Bayer moiré, occured while creating image files at Stanford University Library's Map Scanning Lab and prompted a more focused study. The Bayer moiré defect affects the ability of software to lift features from maps digitally. An analysis of findings has supported developing a better understanding of color filter array technology and some of its associated quality issues: rationales for on-demand file remediation of affected image files, options for map imaging in the future, an effective and open-source approach for vectorization, performance improvements for producing and vectorizing raster images.

An article on this study, authored by Matt Pearson, G. Salim Mohammed, Renzo Sanchez-Silva and Patricia Carbajales, which includes additional quality control measures for imaging large maps and a refinement of the topo raster image specification is now published in the Fall 2013 issue of the Journal of Map & Geography Libraries: Advances in Geospatial Information, Collections & Archives, entitled "Stanford University Libraries Study: Topographical Map Vectorization and the Impact of Bayer Moiré Defect."  For more details please read the article.

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