Automatic extraction of moving objects using multiple features and multiple frames
نویسندگان
چکیده
This paper introduces a novel automatic video object extraction algorithm based on combination of color and motion segmentation results. The algorithm includes five parts: preprocessing, color segmentation, motion segmentation, combination of color and motion segmentation of multiple frames, post-processing. The performance of this algorithm is very promising, resulting in pixel-wise accuracy of extracted objects. Since it is an automatic extraction algorithm, it can be very useful in some real time video processing system based on video objects.
منابع مشابه
Object-Oriented Method for Automatic Extraction of Road from High Resolution Satellite Images
As the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. This processing comprises two fundamental and critical steps towar...
متن کاملA Fall Detection System based on the Type II Fuzzy Logic and Multi-Objective PSO Algorithm
The Elderly health is an important and noticeable issue; since these people are priceless resources of experience in the society. Elderly adults are more likely to be severely injured or to die following falls. Hence, fast detection of such incidents may even lead to saving the life of the injured person. Several techniques have been proposed lately for the fall detection of people, mostly cate...
متن کاملA Novel Method for Tracking Moving Objects using Block-Based Similarity
Extracting and tracking active objects are two major issues in surveillance and monitoring applications such as nuclear reactors, mine security, and traffic controllers. In this paper, a block-based similarity algorithm is proposed in order to detect and track objects in the successive frames. We define similarity and cost functions based on the features of the blocks, leading to less computati...
متن کاملStatistical Background Modeling Based on Velocity and Orientation of Moving Objects
Background modeling is an important step in moving object detection and tracking. In this paper, we propose a new statistical approach in which, a sequence of frames are selected according to velocity and direction of some moving objects and then an initial background is modeled, based on the detection of gray pixel's value changes. To have used this sequence of frames, no estimator or distribu...
متن کاملMoving Objects Tracking Using Statistical Models
Object detection plays an important role in successfulness of a wide range of applications that involve images as input data. In this paper we have presented a new approach for background modeling by nonconsecutive frames differencing. Direction and velocity of moving objects have been extracted in order to get an appropriate sequence of frames to perform frame subtraction. Stationary parts of ...
متن کامل