| Title |
Recognition and Tracking of Moving Objects Using Label-merge Method Based on Fuzzy Clustering Algorithm |
| Authors |
이성민(Seong Min Lee) ; 성일(Il Seong) ; 주영훈(Young Hoon Joo) |
| DOI |
http://doi.org/10.5370/KIEE.2018.67.2.293 |
| Keywords |
Fuzzy C-menas ; FCM ; Clustering ; Cluster ; Object recognition ; Histogram ; Label merge |
| Abstract |
We propose a moving object extraction and tracking method for improvement of animal identification and tracking technology. First, we propose a method of merging separated moving objects into a moving object by using FCM (Fuzzy C-Means) clustering algorithm to solve the problem of moving object loss caused by moving object extraction process. In addition, we propose a method of extracting data from a moving object and a method of counting moving objects to determine the number of clusters in order to satisfy the conditions for performing FCM clustering algorithm. Then, we propose a method to continuously track merged moving objects. In the proposed method, color histograms are extracted from feature information of each moving object, and the histograms are continuously accumulated so as not to react sensitively to noise or changes, and the average is obtained and stored. Thereafter, when a plurality of moving objects are overlapped and separated, the stored color histogram is compared with each other to correctly recognize each moving object. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments. |