Photo Defect Detection for Image Inpainting

Authors:
Rong-Chi Chang;Yun-Long Sie;Su-Mei Chou;Timothy K. Shih
Affiliations:
Asia University, Taichung, Taiwan;Tamkang University, Taiwan;Tamkang University, Taiwan;Tamkang University, Taiwan
Venue:
ISM '05 Proceedings of the Seventh IEEE International Symposium on Multimedia
Year:
2005

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Abstract

Image inpainting (or image completion) techniques use textural or structural information to repair or fill damaged potions of a picture. However, most techniques request a human to identify the portion to be inpainted. We developed a new mechanism which can automatically detect defect portions in a photo, including damages by color ink spray and scratch drawing. The mechanism is based on several filters and structural information of damages. Old photos from the author's family are used for testing. Preliminary results show that most damages can be automatically detected without human involvement. The mechanism is integrated with our inpainting algorithms to complete a fully automatic photo defects repairing system.