Detecting Salient Motion by Accumulating Directionally-Consistent Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
Robust Salient Motion Detection with Complex Background for Real-Time Video Surveillance
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Independent component analysis-based background subtraction for indoor surveillance
IEEE Transactions on Image Processing
An intelligent method to extract characters in color document with highlight regions
IEA/AIE'11 Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part II
Binarization of color document images via luminance and saturation color features
IEEE Transactions on Image Processing
Fast and automatic video object segmentation and tracking for content-based applications
IEEE Transactions on Circuits and Systems for Video Technology
Intelligent moving objects detection via adaptive frame differencing method
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part I
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The detection of moving objects is a critical first step in video surveillance. Numerous background subtraction, frame differencing, optical flow algorithms and a number of post-processing techniques (including noise removal, binary morphological operations, and area thresholding) are used to extract the moving objects. However, these post-processing methods are time consuming and inefficient in real-time applications; for example, noise removal and binary morphological operations require scanning the video frame many times. The study presents an innovative post-processing technique, using bounding-box-based morphological operations, for grouping concentrated connected components and the removal of spread and small connected components for moving objects detection. Results demonstrate that the proposed method is more effective and efficient than traditional post-processing methods.