Objective of Computer Vision
ā¢ The field of computer vision can
be divided into two areas
ā Image enhancement
ā Image analysis
Here we concentrate on fast methods typical for robot soccer and robot
theatre applications
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Computer Vision - Robot Vision and Preception - Lecture Slides, Slides of Computer Science
These are the Lecture Slides of Robot Vision and Preception which includes Transforms, Derived, Fast Fourier, Discrete Fourier Transform, Fast Cosine, Discrete Cosine Transform, Radon Transform, Slant, Karczmarz etc. Key important points are: Computer Vision, Field Of Computer Vision, Divided, Image Enhancement, Image Analysis, Binary Image Processing, Two Gray Levels, Basic Terms, Machine Vision, Aspects
Typology: Slides
2012/2013
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Objective of Computer Vision
- The field of computer vision can
be divided into two areas
- Image enhancement
- Image analysis
Here we concentrate on fast methods typical for robot soccer and robot
theatre applications
Binary image processing ļ® Image with two gray levels 0 and 1 ļ® It contains the basic terms and concepts used in machine vision. ļ® Its techniques are used in all aspects of a vision system. ļ® Small memory requirements ļ® Fast execution time
ļ® Gray level image vs. binary image
POINT
OPERATIONS
Point Operations
Region and segmentation ļ® Region ( ) ļ¬ A subset of an image ļ® Segmentation ļ¬ Grouping of pixels into regions such that
Thresholding
ļ® Three types of thresholding where Z is a set of which elements are integer-valued intervals.
ļ® Original image and its histogram
H
Histogram Equalization
Image notation for soccer ļ® Image : a two-dimensional array of pixels Pixel a[i, j]
Pixel B[i, j]
Geometric properties ļ® In many cases, some simple features of regions are useful to: ļ¬ determine the locations of objects, ļ¬ and to recognize objects. ļ® Geometric properties: ļ¬Size ļ¬Position ļ¬Orientation