Title :
Detection and recognition on parameters of blurred image’s internal structure
Author :
Xu, Gang ; Meng, Xu
Author_Institution :
Sch. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing
Abstract :
The detection of objects, the key technology in the field of image recognition, is the base of accuracy improvement of image recognition process. In this paper, a model is provided for detection and recognition of a blurred imagepsilas internal structure. This model, which is based on moment and Hough, combines geometric features as its parameter identification, and its evaluation criteria is matching percent and algorithm efficiency. The restoration of blurred images and the recognition, position and detection of graphicspsila internal structure can be completed effectively and accurately. In addition, good experimental results were obtained by using this algorithm, even though the objects were covered by each other or nested, which proves the model is applicable on practical application.
Keywords :
geometry; image recognition; image restoration; object detection; blurred image; geometric feature; image recognition; image restoration; object detection; parameter identification; Cybernetics; Image recognition; Image restoration; Machine learning; Object detection; Optical imaging; Parameter estimation; Power engineering and energy; Solid modeling; Wiener filter; Hough; Internal structure; Moment; Recognition of blurred image;
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
DOI :
10.1109/ICMLC.2008.4620889
