Digital Geometric Methods in Image Analysis and Compression

One of the important problems related to image analysis and compression is finding repeated structure. Although the focus of this paper is developing digital geometric models and methods for finding regular structure in digital document images, the applicability of the digital geometric approach is also demonstrated on images taken under orthographic and perspective projection. First, a fast linear-time algorithm is given to compute the static threshold that minimizes the non-welt-composedness or weak connectivity of the document image. Next, a new digital similarity measure is introduced that outperforms the standard similarity measures, including the Hansdorff distance, with respect to determining if two discrete objects in the image are digitizations of the same prototype. This measure is then used in a model-based compression algorithm, and a variation of the algorithm is developed for finding structure in images taken under affine and perspective transformations.

• Type: Conference
• Year: 1998
• Where: ACCV
• Authors: Ari D. Gross, Longin Jan Latecki
• Keywords: ACCV 1998, Computer Vision, Digital Geometric Models, Document Image, Similarity Measures