Image Processing and Pattern Recognition Based on Parallel Shift Technology

209 Pages·2018·8.092 MB·English

by  Bilan, Stepan, Yuzhakov, Sergey

Image Processing and
Pattern Recognition
Based on Parallel Shift Technology

Image Processing and
Pattern Recognition
Based on Parallel Shift Technology
Stepan Bilan
State Economy and Technology University of Transport
Kiev, Ukraine
Sergey Yuzhakov
Gaisin United State Tax Inspection of the
Main Governance of SFS in Vinnytsa Region
Gaisin City, Ukraine
p,
A SCIENCE PUBLISHERS BOOK
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Subjects: LCSH: Computer vision. | Pattern recognition systems. | Parallel
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Preface
The development of computer image processing and recognition systems
is one of the main aspects of artificial intelligence. Currently, there are no
effective methods for video information manipulation other than digital
image processing. A number of alternative methods and algorithms for
processing images based on parallel-shear technology are proposed in
this book. Using these along with digital image processing will enable
the building of a hybrid image processing system. The methods and
algorithms can also be used in analog computers.
The book describes images not in the form of an array of points, but
as a set of functions. Methods and algorithms for image processing have
been developed by analyzing these functions, using these it is possible to
solve the main tasks of image processing. Description of images as a set
of functions allows one to manipulate both raster and non-bitmap images.
Only one quantitative characteristic is analyzed - the area of the image.
The use of parallel shift technology also makes it possible to process
images consisting of irregularly arranged elements. Scientific work is built
in accordance with this classification.
The book is devoted to the development and research of methods of
applying multiple transformations for computer processing and image
recognition. Unlike the known methods, the proposed method uses a
smaller number of the characteristic features to describe images and the
number of computational operations in the system are reduced. Based
on parallel shift technology, a mathematical model of the relationship
between the form of the object and the functions of the intersection area,
was developed. Methods of image recognition, determination of spatial
orientation of objects, parameters of their movement and determination
of the contour of a figure are described in the book. The study of the
efficiency of pattern recognition with various parameters of the input
image, are described.
The book is intended to help researchers in the development of
artificial intelligence, robotics, software and hardware applications.

Contents
Preface v
Introduction xi
1. Feature Extraction Based on Parallel Image Shift Technologies 1
1.1 Fundamentals of Understanding and of Constructing
Images 1
1.2 Image Description 2
1.3 Characteristic Features of Images 5
1.4 Theoretical Description of the Parallel Shift Technology 7
2. Function of the Area of Intersection Formation Based
on Parallel Shift Technology 14
2.1 Mathematical Model of the Image Describing the
Function of the Area of Intersection 14
2.2 Analytical Determination of the Function of the Area of
Intersection of Simple Shapes on the Basic Parameters 18
2.3 Additional Parameters, which Accelerate Plane Image
Recognition Process 25
2.4 Algorithm of Recognition Images Based on PST 29
2.5 Processing of 3D-Objects through PST 33
3. Methods of Pre-Processing Images Based on PST 35
3.1 Edge Detection Method of Plane Figures 37
3.2 Use of Parallel Shift Technology for Noise Removal
in Images 40
3.3 Technical Methods for FAI Preparation 47
3.4 Model for Obtaining FAI of No Bitmap 49
4. Methods of Dynamic Images Processing Based on PST 50
4.1 Determination of Spatial Orientation of Planes 52
viii Image Processing and Pattern Recognition Based on Parallel Shift Technology
4.2 Use of Different Types of Shifts of Image Copies in
Video Processing Devices Based on PST 55
4.3 Methods for Determining Movement Parameters
Using Cyclic Shifts 57
4.4 Methods for Determination of Motion Parameters
Using Non-cyclic Shifts 59
4.5 Methods for Determining Distance of a Moving Object 61
4.6 Comparison of Methods for Determination of Motion
Parameters by Using Different Types of Shifts of the
Image Copy 63
5. Image Processing System Based on PST 65
5.1 System of Perception of Video Information 66
5.2 Saving Template Functions of the Area of Intersection 72
5.3 Application of Image-processing Methods Based on
PST for Prosthetic Visual Organs 77
5.4 Perspective Directions of Image-processing Research
Using PST 80
6. Assessment of Productivity of the Image Processing and
Recognition Systems Based on FAI Analysis 84
6.1 Evaluating the Efficiency of the Chosen Method of
Removing Noise 85
6.2 Determination of the Permissible Error Range of Values
Used to Limit the Maximum Displacement Values 90
6.3 Determination of Values Range of Acceptable Error
Used in Comparison of Integral Coefficients 91
6.4 Determination of Range Values of Acceptable Error in
Comparison of FAI on a Detailed Stage of the Analysis
of Image Recognition 93
6.5 Evaluating the Effectiveness of Image Recognition
Process in Various Parameters of Input Information
Using Calculated Values of Permissible Errors 94
7. Hardware Implementation of the Image Recognition
System Based on Parallel Shift Technology 101
7.1 Generalised Model of Image Recognition System Based
on Parallel Shift Technology 101
7.2 Selecting a Cover for Representing the Image in the
Recognition System 102
7.3 Hardware Implementation of Parallel Shift and
Computation of the Area of Intersection of Images 104
7.4 Modelling of the Main Hardware Modules for
Determining FAI in Modern CAD Systems 113
Contents ix
7.5 Selection and Storage of Patterns in UMFP 118
7.6 Optical Image Recognition System Based on Parallel
Shift Technology 120
8. Methodology of Experimental Studies in Recognition Process
Based on Parallel Shift Technology 126
8.1 Selection and Analysis of Characteristic Features of
Images Based on Parallel Shift Technology 126
8.2 Analysis of the Accuracy of Image Recognition, Based
on the Obtained FAI 131
8.3 Description of Image with the Help of Quantitative
Characteristics of the Basic Properties of FAI 148
8.4 Experimental Analysis of FAI of Patterns Image 157
8.5 The Sequence of Steps for Using Parallel Shift
Technology to Describe and Recognise Images 163
8.6 Advantages of Text Recognition Based on Parallel
Shift Technology 166
References 187
Index 192