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楼主: Interjection
发表于 2025-3-28 17:30:12 | 显示全部楼层
https://doi.org/10.1007/978-1-4302-3199-8 have been developed for automatic indexing and retrieval in document databases. Most of these use indexes depending on the textual content of documents, and very few are able to handle graphical or image content without human annotation..This paper describes an approach similar to the bag of words
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A Vectorization System for Architecture Engineering Drawingscognize graphic objects in the order of increasing characteristic complexity and progressively simplify the drawing image by removing recognized objects from it. Various recognition algorithms for basic graphic types have been developed and efficient interactive recognition methods are proposed as c
发表于 2025-3-29 08:39:48 | 显示全部楼层
Musings on Symbol Recognitione variety of contributions. We then propose some interesting challenges for symbol recognition research in the present years, including symbol spotting methods, recognition procedures for complex symbols, and a systematic approach to performance evaluation of symbol recognition methods.
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Symbol Recognition Combining Vectorial and Statistical Features we overcome deficiencies of each method taken alone. Indeed, a Region Adjacency Graph of loops is associated with a graph of vectorial primitives. Thus, a loop is both representend in terms of its boundaries and its content. Some preliminary results are provided thanks to the evaluation protocol es
发表于 2025-3-30 02:03:52 | 显示全部楼层
Segmentation and Retrieval of Ancient Graphic Documents approach aimed at segmenting the graphical part in historical heritage called . and extracting its signatures in order to develop a Content-Based Image Retrieval (CBIR) system. The research principle is established on the concept of invariant texture analysis (Co-occurrence and Run-length matrices,
发表于 2025-3-30 06:14:20 | 显示全部楼层
A Method for 2D Bar Code Recognition by Using Rectangle Features to Allocate Vertexeschieving high recognition rate. This method includes three steps. The first step is to find out the four vertexes of ROI (Regions Of Interest); the second is a geometric transform to form an upright image of ROI; the third is to restore a bilevel image of the upright image. This work is distinguishe
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