tailieunhanh - Báo cáo hóa học: " A Method for Single-Stimulus Quality Assessment of Segmented Video"

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: A Method for Single-Stimulus Quality Assessment of Segmented Video | Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volume 2006 Article ID 39482 Pages 1-22 DOI ASP 2006 39482 A Method for Single-Stimulus Quality Assessment of Segmented Video R. Piroddi1 and T. Vlachos2 1 Department of Electrical and Electronic Engineering Imperial College London Exhibition Road London SW7 2AZ UK 2 Centre for Vision Speech and Signal Processing CVSSP School of Electronics and Physical Sciences University of Surrey Guildford GU2 7XH UK Received 17 March 2005 Revised 11 July 2005 Accepted 31 July 2005 We present a unified method for single-stimulus quality assessment of segmented video. This method takes into consideration colour and motion features of a moving sequence and monitors their changes across segment boundaries. Features are estimated using a local neighbourhood which preserves the topological integrity of segment boundaries. Furthermore the proposed method addresses the problem of unreliable and or unavailable feature estimates by applying normalized differential convolution NDC . Our experimental results suggest that the proposed method outperforms competing methods in terms of sensitivity as well as noise immunity for a variety of standard test sequences. Copyright 2006 Hindawi Publishing Corporation. All rights reserved. 1. INTRODUCTION Object-based descriptions of still images and moving sequences are becoming increasingly important for multimedia and broadcasting applications offering many well-documented advantages 1 . Such descriptions allow the authoring manipulation editing and coding of digital imagery in a far more creative intuitive efficient and user-friendly manner compared to conventional frame-based alternatives. A key tool towards the identification of objects or regions of interest is segmentation which has emerged as a very active area of research in the past 20 years. Segmentation has often been regarded as a first step towards automated image analysis with applications in scene .

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