Content introduction chapter development of a complex image processing method

CONTENT
INTRODUCTION………………………………………………………………...2
CHAPTER 1 . DEVELOPMENT OF A COMPLEX IMAGE PROCESSING METHOD………………………………………………………………………….4
1.1 The concept of image processing. Choice of software implementation environment………………………………………………………………………...4
1.2 Choice of image processing and segmentation methods……………………….5
CHAPTER 2. MODALITY OF SYNTACTIC STRUCTURES IN THE TEXT……………………………………………………………………………..14
2.1 The characterising function of modality text………………………………….14
2.2 Modality text syntactic structure……………………………………………...17
CONCLUSION…………………………………………………………………..26
LIST OF SOURCES USED……………………………………………………...28


INTRODUCTION
To date, there are many tools and software systems for image processing. Most of them are narrowly focused, but nevertheless the general range of issues they consider is very large. These are the main filtering methods, and wavelet transforms, and methods for improving, restoring and compressing images, and so on. All these processing methods and others are actively used in everyday life. For example, in medicine, in the military field, in machine vision, in systems based on human biometric data (scanning of the retina, iris, fingerprints, and so on), in image segmentation tasks.
Image segmentation is understood as the division of the original image into its constituent regions or objects. This approach to image processing has found very wide application today.
The task of image segmentation itself is one of the most difficult tasks in image processing. The final result is often determined by the accuracy of segmentation, so when choosing one or another segmentation method, great attention should be paid to the reliability of the algorithm. However, there is no single, generally accepted approach that would underlie most algorithms. There is also no single algorithm that would allow for acceptable segmentation for any image. This is one of the difficulties of segmentation, and this is the reason for the large number of different approaches to solving these image processing problems.
The purpose of the course work is the software implementation of methods for segmenting images of textual information on images of banknotes.
To achieve this goal, the following tasks are formed:
- study of the generalized theoretical part of image processing;
- mastering various methods of segmentation of textual information in images;
- definition in the graphics editor, what methods are needed to improve the quality of image data for further conversion;
- implementation in a high-level language of the application, which allows filtering with given images;
- testing the developed program and comparing the results.
To develop the application, the Borland C++ Builder programming environment will be used.