scholarly journals Infrared Moving Multi-Target Tracking Based on Particle Filter and FCM

2013 ◽  
Vol 347-350 ◽  
pp. 3792-3796
Author(s):  
Fan Jun Hu ◽  
Wen Jun Shi
Keyword(s):  
Particle Filter ◽  
Target Tracking ◽  
Median Filter ◽  
Infrared Image ◽  
Image Sequences ◽  
Fcm Algorithm ◽  
Efficient Approach ◽  
Morphological Filtering ◽  
Multi Target Tracking ◽  
Island Shore

An efficient approach based on particle filter and FCM is presented to realize moving infrared multi-target tracking under Island shore background. Some possible targets can be obtained and saved by processing IR data through denoising by median filter, extracting edge, identifying and eliminating sea-sky line, morphological filtering and etc. Data association and robust multi-target tracking can be realized by the proposed particle filter and FCM algorithm. The proposed approach is validated to track multi-target effectively by using actual infrared image sequences with Island shore background. Experiment results indicate the feasibility and effectiveness of the proposed method.

scholarly journals A Study of LM-IHPDA Algorithm for Multi-Target Tracking in Infrared Image Sequences

2013 ◽  
Vol 19 (3) ◽  
pp. 209-218 ◽  
Author(s):  
Tae Han Kim ◽  
Byung In Choi ◽  
Ji Eun Kim ◽  
Yu Kyung Yang ◽  
Taek Lyul Song
Keyword(s):  
Target Tracking ◽  
Infrared Image ◽  
Image Sequences ◽  
Multi Target Tracking

scholarly journals Novel Spatiotemporal Filter for Dim Point Targets Detection in Infrared Image Sequences

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Zhaohui Li ◽  
Xiaorui Wang ◽  
Jianqi Zhang ◽  
Delian Liu
Keyword(s):  
Median Filter ◽  
Infrared Image ◽  
Local Maximum ◽  
Texture Features ◽  
Pulse Signal ◽  
Image Sequences ◽  
Maximum Point ◽  
Isolated Points ◽  
Temporal Profiles ◽  
Moving Patterns

Dim point target detection is of great importance in both civil and military fields. In this paper a novel spatiotemporal filter is proposed to incorporate both the spatial and temporal features of moving dim point targets. Since targets are expected to be detected as far as possible, in this situation, they have no texture features in spatial dimensions, appearing like isolated points. Based on the attributes, potential targets are extracted by searching the local maximum point in a sliding window. And the potential targets are then correlated based on target moving patterns. After combining local maximum points and target moving patterns, structure background in infrared scene is removed. Next, the temporal profiles of infrared sense are reviewed and examined. By a new max-median filter performing on temporal profiles, the intensity of target pulse signal is extracted. Finally, each temporal profile is divided into several pieces to estimate the variance of the temporal profiles, which leads to a new detection metric. The proposed approach is tested via several infrared image sequences. The results show that our proposed method can significantly reduce the complex background in aerial infrared image sequence and have a good detection performance.

Multi-Target Tracking Based on Optimized Particle Filter Algorithm

2012 ◽  
Vol 11 (1) ◽  
pp. 630-633
Author(s):  
Junying Meng ◽  
Jiaomin Liu ◽  
Juan Wang ◽  
Ming Han
Keyword(s):  
Particle Filter ◽  
Target Tracking ◽  
Multi Target Tracking ◽  
Particle Filter Algorithm
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