Paper
30 October 2012 Visual scene busyness measures through a region growing spatial segmentation
Author Affiliations +
Abstract
This paper proposes a visual scene busyness indicator obtained from the properties of a full spatial segmentation of static images. A fast and effective region merging scheme is applied for this purpose. It uses a semi-greedy merging criterion and an adaptive threshold to control segmentation resolution. The core of the framework is a hierarchical parallel merging model and region reduction techniques. The segmentation procedure consists of the following phases: 1. algorithmic region merging, and 2. region reduction, which includes small segment reduction and enclosed region absorption. Quantitative analyses on standard benchmark data have shown the procedure to compare favourably to other segmentation methods. Qualitative assessment of the segmentation results indicate approximate semantic correlations between segmented regions and real world objects. This characteristic is used as a basis for quantifying scene busyness in terms of properties of the segmentation map and the segmentation process that generates it. A visual busyness indicator based on full colour segmentation is evaluated against conventional measures.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gaurav Gupta, Alexandra Psarrou, Sophie Triantaphillidou, and Jae-Young Park "Visual scene busyness measures through a region growing spatial segmentation", Proc. SPIE 8546, Optics and Photonics for Counterterrorism, Crime Fighting, and Defence VIII, 85460P (30 October 2012); https://doi.org/10.1117/12.974760
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image segmentation

Visualization

Digital filtering

Silicon

Image filtering

Bismuth

Einsteinium

RELATED CONTENT


Back to Top