tailieunhanh - Báo cáo hóa học: "Editorial Performance Evaluation in Image Processing"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Editorial Performance Evaluation in Image Processing | Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volume 2006 Article ID 45742 Pages 1-3 DOI ASP 2006 45742 Editorial Performance Evaluation in Image Processing Michael Wirth Matteo Fraschini Martin Masek and Michel Bruynooghe Department of Computing and Information Science University of Guelph Guelph ON Canada N1G2W1 Received 3 April 2006 Accepted 3 April 2006 Copyright 2006 Michael Wirth et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. The scanning and computerized processing of images had its birth in 1956 at the National Bureau of Standards NBS now National Institute of Standards and Technology NIST 1 . Image enhancement algorithms were some of the first to be developed 2 . Half a century later literally thousands of image processing algorithms have been published. Some of these have been specific to certain applications such as the enhancement of latent fingerprints whilst others have been more generic in nature applicable to all yet master of none. The scope of these algorithms is fairly expansive ranging from automatically extracting and delineating regions of interest such as in the case of segmentation to improving the perceived quality of an image by means of image enhancement. Since the early years of image processing as in many subfields of software design there has been a portion of the design process dedicated to algorithm testing. Testing is the process of determining whether or not a particular algorithm has satisfied its specifications relating to criteria such as accuracy and robustness. A major limitation in the design of image processing algorithms lies in the difficulty in demonstrating that algorithms work to an acceptable measure of performance. The purpose of algorithm testing is two-fold. Firstly it provides either a qualitative or a .

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