Recovering and Characterizing Image Features Using An Efficient Model Based Approach

Раздел: Статьи

Blaszka Thierry,Deriche Rachid

Recovering and Characterizing Image Features Using An Efficient Model Based Approach

Category:
Keywords: Low-Level Image Processing,Physics of Image Formation

abstract:

Edges, corners and vertices are strong and useful features in computer vision. This paper deals with the development of an efficient model based approach in order to detect and characterize precisely these important features. The key of our approach is r st to propose some efficient models associated to each of these features and second to efficiently extract and characterize these features directly from the image. The models associated to each feature include a large number of intrinsic parameters (Grey level intensities, location, orientation of the line segments ) but also an important parameter which is associated to the blurring effect due to the acquisition system. The important problem of the initialization phase in the minimization process is al so considered and an original and efficient solution is proposed. In order to test and compare the reliability, the robustness and the efficiency of the different proposed approaches, a large number of experiments involving noisy synthetic data and real images have been carried out. Finally, a comparative study of this approach and the classic corner operators is presented

На статью

Graphics & Media Lab. >> Библиотека | Курсы | Графикон

Верстка, дизайн, программирование Людмила Попова
Выпускающий редактор Дмитрий Ватолин
Подготовка материала Ольга Карпенко