Paper
7 May 2007 Adaptive target segmentation using runtime-weighted features
Author Affiliations +
Abstract
Target segmentation plays an important role in the entire target tracking process. This process decides whether the current pixel belongs to the target region or not. In the previous works, the target region was extracted according to whether the intensity of each pixel is larger than a certain value. But simple binarization using one feature, i.e. intensity, can easily fail to track as condition changes. In this paper, we employ more features such as intensity, deviation over time duration, matching error, etc. rather than intensity only and each feature is weighted by the weighting logic, which compares the characteristics in the target region with that in the background region. The weighting logic gives a higher weight to the feature which has a large difference between the target region and the background region. So the proposed segmentation method can control the priority of features adaptively and is robust to the condition changes of various circumstances.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jik-Han Jung, Hwal-Suk Lee, Dong-Jo Park, Chang-Han Park, and Jae-Ik Lee "Adaptive target segmentation using runtime-weighted features", Proc. SPIE 6567, Signal Processing, Sensor Fusion, and Target Recognition XVI, 65671F (7 May 2007); https://doi.org/10.1117/12.719293
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image segmentation

Filtering (signal processing)

Logic

Cameras

Electronic filtering

Optical filters

Motion models

Back to Top