Download Analysis of Engineering Drawings and Raster Map Images by Thomas C. Henderson PDF

By Thomas C. Henderson

This publication covers updated tools and algorithms for the automatic research of engineering drawings and electronic cartographic maps. The Non-Deterministic Agent process (NDAS) deals a parallel computational method of such picture research. The ebook describes suggestions compatible for power and particular wisdom illustration for engineering drawings and electronic maps. It additionally highlights extra particular ideas, e.g., making use of robotic navigation and mapping how you can this challenge. additionally integrated are extra distinct debts of using unsupervised segmentation algorithms to map photos. eventually, these types of threads are woven jointly in comparable structures: NDAS and AMAM (Automatic Map research Module).

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The exploitation of this information will be further elucidated in following chapters. Chapter 3 Text and Graphics Analysis in Engineering Drawings The meaning of an engineering drawing is expressed through text and graphics and the relations between them. Chapter 1 provided a detailed summary of the major approaches to their segmentation, and here we describe our own contributions on some specific applications. The goal is the fully automatic segmentation of text and graphics in an engineering drawing image, as well as its interpretation; that is, characters represented as pixels must be interpreted as to which specific character they represent.

25) line segment1: enforces distinct instance of line segment. (26) line segment2: enforces distinct instance of line segment. (27) line segment3: enforces distinct instance of line segment. (28) text1: enforces distinct instance of text. (29) text2: enforces distinct instance of text. (30) symmetric pointer pair in: 2 collinear pointer rays with arrows at near ends. These will point inward toward dimension lines. (31) symmetric pointer pair out: 2 collinear pointer rays with arrows at distant ends.

Xu also developed methods for linear feature extraction. As described in Chap. 1, much work has been done on this topic, and our method can be viewed as an extension of the Zig-Zag method of Dori [30]. The mobile robot mapping approach exploits the Generalized Voronoi Diagram (GVD) [12]. After constructing the GVD, linear segments are found by using the differential GVD curvature. In the free space of a plane with a set of obstacles, the Voronoi diagram (VD) [24] is defined as a collection of line segments or convex polygons that partition free space into n cells so that each cell contains one obstacle.

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