Title :
Accurate detection and complete shape extraction of sand-flies using Gaussian mixture model
Author :
Machraoui, Ahmed Nejmedine ; Diouani, Mohamed Fethi ; Ghrab, Jamila ; Sayadi, Mounir
Author_Institution :
Lab. of Signal Image & Energy Mastery (SIME), Univ. of Tunis, Tunis, Tunisia
Abstract :
This paper presents a method for the accurate detection of the positions of moving phlebotomenae (sand-flies), and the extraction of their complete shape. The proposed method is based on the background subtraction approach, with a statistical background model found using Gaussian mixture model. Furthermore, a method based on the maximization of interclass variance, is used to eliminate wings of the phlebotomenae and then detect accurately its position. Results are further used to study the behaviour of phlebotomenae, and subsequently, improve the traps to fight against many diseases transmitted by these insects, especially leishmaniasis. The experimental results show the efficiency of the proposed algorithm to accurately detect the position and extract the complete shape of moving phlebotomenaes even in case of very blurry ones.
Keywords :
Gaussian processes; biology computing; mixture models; object detection; optimisation; shape recognition; Gaussian mixture model; background subtraction approach; interclass variance maximization; phlebotomenae; sand-flies detection; sand-flies shape extraction; statistical background model; Conferences; Diseases; Hidden Markov models; Insects; Shape; Statistics; Tracking; EM algorithm; Gaussian Mixture Model; Motion detection; Video tracking; background subtraction;
Conference_Titel :
Image Processing, Applications and Systems Conference (IPAS), 2014 First International
Print_ISBN :
978-1-4799-7068-1
DOI :
10.1109/IPAS.2014.7043277