Download e-book for iPad: An Introduction to Object Recognition: Selected Algorithms by Marco Alexander Treiber
By Marco Alexander Treiber
Rapid improvement of computing device has enabled utilization of computerized item acceptance in progressively more functions, starting from commercial photo processing to scientific purposes, in addition to initiatives caused by way of the common use of the net. every one region of software has its particular standards, and for that reason those can't all be tackled adequately by way of a unmarried, general-purpose set of rules.
This easy-to-read text/reference presents a accomplished creation to the sphere of item reputation (OR). The ebook provides an outline of the various functions for OR and highlights vital set of rules sessions, offering consultant instance algorithms for every category. The presentation of every set of rules describes the elemental set of rules circulate intimately, whole with graphical illustrations. Pseudocode implementations also are incorporated for plenty of of the tools, and definitions are provided for phrases that may be surprising to the amateur reader. helping a transparent and intuitive instructional kind, using arithmetic is saved to a minimum.
Topics and features:
- Presents instance algorithms masking international ways, transformation-search-based tools, geometrical version pushed equipment, 3D item popularity schemes, versatile contour becoming algorithms, and descriptor-based methods
- Explores each one procedure in its entirety, instead of concentrating on person steps in isolation, with a close description of the move of every set of rules, together with graphical illustrations
- Explains the real ideas at size in a simple-to-understand type, with a minimal utilization of mathematics
- Discusses a huge spectrum of functions, together with a few examples from advertisement products
- Contains appendices discussing subject matters with regards to OR and general within the algorithms, (but no longer on the center of the equipment defined within the chapters)
Practitioners of business snapshot processing will locate this straightforward advent and evaluation to OR a precious reference, as will graduate scholars in computing device imaginative and prescient courses.
Marco Treiber is a software program developer at ASM meeting structures, Munich, Germany, the place he's Technical Lead in snapshot Processing for the imaginative and prescient process of SiPlace placement machines, utilized in SMT assembly.
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Additional resources for An Introduction to Object Recognition: Selected Algorithms for a Wide Variety of Applications
For each geometric form, the fixed-length distance function can be regarded as a distinctive feature vector. In order to increase performance, this vector is transformed to Fourier space. ,  or ) is a very Fig. 2 Global Feature Vectors 29 compact representation of the data. Just a few Fourier coefficients are sufficient for a distinctive description if we deal with “simple” objects. , calculating the Euclidean distance of the Fourier-transformed feature vector of a scene object to the known Fourier-transformed feature vectors of the prototypes.
If the value of the maximum exceeds a certain threshold value t, a valid object instance is found. Its position is defined by the position of the maximum. The whole process is illustrated by a schematic example in Fig. 1: There, a 3 × 3 template showing a cross (in green, cf. lower left part) is shifted over an image of 8 × 8 pixel size. At each position, the value of the cross-correlation coefficient is calculated and these values are collected in a 2D matching function (here of size 6 × 6, see right part.
This is done by exploring the so-called transformation space, which comprises the set of all possible transform parameter combinations. Each parameter combination defines a transformation between the model data and the scene image. The aim is to find a combination which maximizes M. 1007/978-1-84996-235-3_3, C Springer-Verlag London Limited 2010 41 42 3 Transformation-Search Based Methods the similarity (or minimizes a distance, respectively). , the searched object is actually present at the position defined by the transformation parameters.
An Introduction to Object Recognition: Selected Algorithms for a Wide Variety of Applications by Marco Alexander Treiber