Search for: simple-and-efficient-algorithms
Article Proceedings of the 3rd International Conference on Computer and Knowledge Engineering, ICCKE 2013, Mashhad: Iran ; 2013 , Pages 219-222 ; 9781479920921 (ISBN) ; Pourreza, M ; Banaee, T ; Sharif University of Technology
Retinal vessels tortuosity is one of the important signs of cardiovascular diseases such as diabetic retinopathy and hypertension. In this paper we present a simple and efficient algorithm to measure the grade of tortuosity in retinal images. This algorithm consists of four main steps,vessel detection, extracting vascular skeleton via thinning, detection of vessel crossovers and bifurcations and finally calculating local and global tortuosity. The last stage is based on a circular mask that is put on every skeleton point of retinal vessels. While the skeleton of vessel splits the circle in each position, the local tortuosity is considered to be the bigger to smaller area ratio. The proposed...
An efficient hybrid approach based on K-means and generalized fashion algorithms for cluster analysis, Article 2015 AI and Robotics, IRANOPEN 2015 - 5th Conference on Artificial Intelligence and Robotics, Qazvin, Iran, 12 April 2015 ; April , 2015 , Page(s): 1 - 7 ; 9781479987337 (ISBN) ; Ramezanian, R ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc 2015
Clustering is the process of grouping data objects into set of disjoint classes called clusters so that objects within a class are highly similar with one another and dissimilar with the objects in other classes. The k-means algorithm is a simple and efficient algorithm that is widely used for data clustering. However, its performance depends on the initial state of centroids and may trap in local optima. In order to overcome local optima obstacles, a lot of studies have been done in clustering. The Fashion Algorithm is one effective method for searching problem space to find a near optimal solution. This paper presents a hybrid optimization algorithm based on Generalized Fashion Algorithm...
Article IET Image Processing ; Volume 10, Issue 3 , 2016 , Pages 235-246 ; 17519659 (ISSN) ; Tabandeh, M ; Gholampour, I ; Sharif University of Technology
Institution of Engineering and Technology 2016
In visual surveillance, detecting and localising abnormal events are of great interest. In this study, an unsupervised method is proposed to automatically discover abnormal events occurring in traffic videos. For learning typical motion patterns occurring in such videos, a group sparse topical coding (GSTC) framework and an improved version of it are applied to optical flow features extracted from video clips. Then a very simple and efficient algorithm is proposed for GSTC. It is shown that discovered motion patterns can be employed directly in detecting abnormal events. A variety of abnormality metrics based on the resulting sparse codes for detection of abnormality are investigated....