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학술지 A Novel Monochromatic Cue for Detecting Regions of Visual Interest
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정찬호, 김원준, 유승우, 김창익
Image and Vision Computing, v.32 no.6-7, pp.405-413
Finding regions of interest (ROIs) is a fundamentally important problem in the area of computer vision and image processing. Previous studies addressing this issue have mainly focused on investigating chromatic cues to characterize visually salient image regions, while less attention has been devoted to monochromatic cues. The purpose of this paper is the study of monochromatic cues, which have the potential to complement chromatic cues, for the detection of ROIs in an image. This paper first presents a taxonomy of existing ROI detection approaches using monochromatic cues, ranging from well-known algorithms to the most recently published techniques. We then propose a novel monochromatic cue for ROI detection. Finally, a comparative evaluation has been conducted on large scale challenging test sets of real-world natural scenes. Experimental results demonstrate that the use of our proposed monochromatic cue yields a more accurate identification of ROIs. This paper serves as a benchmark for future research on this particular topic and a steppingstone for developers and practitioners interested in adopting monochromatic cues to ROI detection systems and methodologies. © 2014 Elsevier B.V.
KSP 제안 키워드
Comparative Evaluation, Computer Vision(CV), Detection Approaches, Intrusion detection system(IDS), Natural scene, Real-world, Regions of interest, Salient image regions, computer vision and image processing, large-scale