@incollection{furht_photo_2008,
	title = {Photo {Defect} {Detection}},
	copyright = {©2008 Springer-Verlag},
	isbn = {978-0-387-74724-8 978-0-387-78414-4},
	url = {http://link.springer.com/referenceworkentry/10.1007/978-0-387-78414-4_179},
	abstract = {DefinitionImage inpainting techniques include photo defect detection, where ink traces, scratch, and damage from ink pens are automatically detected.The concept of image inpainting is discussed in the article entitled “Digital Inpainting.” Most existing inpainting mechanisms allow users to select a defect area or a mask of object to be removed. To cope with the inconveniency, we developed a nave photo defect detection mechanism. Ink traces, scratch, and damage from ink pens are automatically detected. We consider the intensity and shape of photo defects. Though, it is almost not possible to discriminate ink regions from objects in photos. The intensity variation of ink regions is usually quite smooth and steady while comparing with objects in photos. Thus, we use the HSI color space and use intensity in the first filter. In the second filter, we record the number of pixels been detected in each intensity variation. We calculate the variance of pixel numbers detected between t ...},
	language = {en},
	urldate = {2016-05-03},
	booktitle = {Encyclopedia of {Multimedia}},
	publisher = {Springer US},
	editor = {Furht, Borko},
	year = {2008},
	note = {00000},
	pages = {726--727}
}

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