ПОИСК МЕДИЦИНСКИХ ИЗОБРАЖЕНИЙ ПО СОДЕРЖАНИЮ В УСЛОВИЯХ ШУМОВ

На примере задачи поиска магнитно-резонансных томографических (МРТ) изображений мозга проводится оценка влияния различных шумовых факторов, вида дескрипторов изображений, а также значений управляющих параметров на результаты поиска медицинских изображений по образцу. Приводятся результаты экспериментальных исследований и даются рекомендации по выбору типа дескрипторов МРТ-изображений мозга

Colour Texture analysis

This chapter presents a novel and generic framework for image segmentation using a compound image descriptor that encompasses both colour and texture information in an adaptive fashion. The developed image segmentation method extracts the texture information using low-level image descriptors (such as the Local Binary Patterns (LBP)) and colour information by using colour space partitioning. The main advantage of this approach is the analysis of the textured images at a micro-level using the local distribution of the LBP values, and in the colour domain by analysing the local colour distribution obtained after colour segmentation. The use of the colour and texture information separately has proven to be inappropriate for natural images as they are generally heterogeneous with respect to colour and texture characteristics. Thus, the main problem is to use the colour and texture information in a joint descriptor that can adapt to the local properties of the image under analysis. We will review existing approaches to colour and texture analysis as well as illustrating how our approach can be successfully applied to a range of applications including the segmentation of natural images, medical imaging and product inspection

Fingerprint Recognition using Gray Level Co-Occurrence Matrices (GLCM) and Discrete Wavelet Transform (DWT)

This paper is thoroughly investigated regarding the fingerprint recognition techniques. This is because the world of security had become more essential. Thus, fingerprint recognition is one of the security enforcement and needed to be developed essentially. This project is focused on the effectiveness of the Gray-Level Co-occurrence Matrices (GLCM) and Discrete Wavelet Transform (DWT) techniques for fingerprint recognition. As in the chapter one, this paper discusses regarding the background of the GLCM and the DWT as well as the reason of this project was initiated. Other than that, this paper also discuss regarding the problem that had been faced previously in order to recognise fingerprint optimally. This paper also discusses the objectives and the limitation of this project in this chapter. On the next chapter, history regarding the GLCM as well as DWT had been widely discuss that made the fingerprint recognition system becomes more popular nowadays. The definition of term, equation and equation related to the GLCM and DWT also had been explained. Moreover, some previous related study will also be discussed. On the third chapter, this paper reviews the method that will be approached for the project for the entire eight months’ timeframe. As for the last chapter, several initial conclusions had been made regarding the fingerprint recognition techniques

Fingerprint Recognition using Gray Level Co-Occurrence Matrices (GLCM) and Discrete Wavelet Transform (DWT)

This paper is thoroughly investigated regarding the fingerprint recognition techniques. This is because the world of security had become more essential. Thus, fingerprint recognition is one of the security enforcement and needed to be developed essentially. This project is focused on the effectiveness of the Gray-Level Co-occurrence Matrices (GLCM) and Discrete Wavelet Transform (DWT) techniques for fingerprint recognition. As in the chapter one, this paper discusses regarding the background of the GLCM and the DWT as well as the reason of this project was initiated. Other than that, this paper also discuss regarding the problem that had been faced previously in order to recognise fingerprint optimally. This paper also discusses the objectives and the limitation of this project in this chapter. On the next chapter, history regarding the GLCM as well as DWT had been widely discuss that made the fingerprint recognition system becomes more popular nowadays. The definition of term, equation and equation related to the GLCM and DWT also had been explained. Moreover, some previous related study will also be discussed. On the third chapter, this paper reviews the method that will be approached for the project for the entire eight months’ timeframe. As for the last chapter, several initial conclusions had been made regarding the fingerprint recognition techniques

Image Retreival Using Weighted Color Co-occurrence Histogram

Color image retrieval is to search color images using queries represented by image descriptors, which usually describe color distribution and relation of color pixels in an image. A color co-occurrence histogram (CCH) among the descriptors captures information on the spatial layout of colors within an image. It has shown excellent performance on color image retrieval, but requires many bins to describe contents of images and has bad effect on the similarity of same contents images, in which the size of homogeneous color regions are highly different. To resolve these problems and to improve retrieval performance, this thesis proposes a weighted CCH and two image retrieval methods using it. Generally the process of image retrieval using a CCH has three steps. The first step is to get the CCH from a query image. The second step is to compute similarity between CCHs of the query image and reference images. The last step is to sort reference images by the similarities and to visualize them. The proposed retrieval methods weight main diagonal and off-diagonal elements of a CCH in the first and/or the second steps mentioned above. Experiments have shown that the proposed methods with a few bins outperform some conventional methods when large weight is given on off-diagonal elements regardless of color quantization levels. We believe that the effectiveness of the method is caused by the characteristics describing the size and the coherence of homogeneous color regions and being robust to size variation of the color regions. Moreover, the image retrieval performance is little affected by the threshold, which is an energy level of valid bins, regardless of color quantization levels. The proposed methods use contents of images effectively, so they can be effectually used in the other content-based applications such as color image classification, color object tracking, and video cut detection.제１장 서 론 = 1 1.1 연구의 배경 = 1 1.2 제안한 방법 = 3 제２장 내용기반 영상검색을 위한 컬러 기술자 = 6 2.1 내용기반 영상검색 시스템 = 6 2.2 컬러영상을 위한 기술자 = 7 제３장 컬러 동시발생 히스토그램에 의한 영상검색 = 19 3.1 컬러 동시발생 히스토그램의 문제점 = 19 3.2 대각성분과 비대각성분의 영상기술 = 24 3.3 대각성분과 비대각성분의 영상검색 성능 = 29 제４장 가중치를 둔 컬러 동시발생 히스토그램을 이용한 영상검색 = 36 4.1 대각성분 및 비대각성분에 가중치를 둔 영상검색 = 38 4.1.1 대각성분 및 비대각성분에 가중치를 둔 CCH = 38 4.1.2 빈 개수 축소와 유사도 측정 = 42 4.2 대각성분, 비대각성분 및 가중치에 의한 영상검색 = 46 4.2.1 CCH의 획득과 빈 제거 = 46 4.2.2 유사도 측정 = 48 제５장 실험 및 고찰 = 52 5.1 실험환경 및 성능평가 방법 = 52 5.2 실험결과 및 고찰 = 55 제６장 결 론 = 79 참고 문헌 = 8