A fuzzy vessel tracking algorithm for retinal images based on fuzzy clustering

1998 ◽  
Vol 17 (2) ◽  
pp. 263-273 ◽  
Author(s):  
Y.A. Tolias ◽  
S.M. Panas
Keyword(s):  
Fuzzy Clustering ◽  
Tracking Algorithm ◽  
Retinal Images ◽  
Vessel Tracking

Vessel Tracking Algorithm using Multiple Local Smooth Paths

2016 ◽  
Vol 53 (6) ◽  
pp. 137-145
Author(s):  
Byunghwan Jeon ◽  
Yeonggul Jang ◽  
Dongjin Han ◽  
Hackjoon Shim ◽  
Hyungbok Park ◽  
...  
Keyword(s):  
Tracking Algorithm ◽  
Vessel Tracking

Adaptive Tracking Algorithm of Multi-Target Based on Fuzzy Clustering

2014 ◽  
Vol 513-517 ◽  
pp. 448-452
Author(s):  
Xiu Hua Hu ◽  
Lei Guo ◽  
Hui Hui Li
Keyword(s):  
State Estimation ◽  
Target Tracking ◽  
Fuzzy Clustering ◽  
Tracking System ◽  
Joint Probability ◽  
Tracking Algorithm ◽  
Adaptive Tracking ◽  
Correlation Criterion ◽  
Multi Target Tracking ◽  
Fuzzy Clustering Theory

For multi-target tracking system, aiming at solving the problem of low precision of state estimation caused by the data correlation ambiguity, the paper presents a novel multi-sensor multi-target adaptive tracking algorithm based on fuzzy clustering theory. Based on the joint probability data association algorithm, the new approach takes account of the case that whether the measure is validated and its possibility of belong to false alarm, and improves the correlation criterion of effective measurement with existing track on the basis of fuzzy clustering theory, which all perfect the update equation of target state estimation and the covariance. Meanwhile, with the adaptive distributed fusion processing structure, it enhance the robustness of the system and without prejudice to the real-time tracking. With the simulation case studies of radar/infrared sensor fusion multi-target tracking system, it verifies the effectiveness of the proposed approach.

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