Basic Image Features (BIFs) Arising from Approximate Symmetry Type

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• 作者：Lewis D. Griffin ; Martin Lillholm ; Mike Crosier ; Justus van Sande
• 关键词：Gaussian Derivatives ; Hermite Transform ; Group Theory
• 刊名：Lecture Notes in Computer Science
• 出版年：2009
• 出版时间：2009
• 年：2009
• 卷：5567
• 期：1
• 页码：343-355
• 全文大小：3.5 MB

文摘

We consider detection of local image symmetry using linear filters. We prove a simple criterion for determining if a filter is sensitive to a group of symmetries. We show that derivative-of-Gaussian (DtG) filters are excellent at detecting local image symmetry. Building on this, we propose a very simple algorithm that, based on the responses of a bank of six DtG filters, classifies each location of an image into one of seven Basic Image Features (BIFs). This effectively and efficiently realizes Marr’s proposal for an image primal sketch. We summarize results on the use of BIFs for texture classification, object category detection, and pixel classification.