A new interframe coding scheme using the effective representation of frame difference image

2003 ◽  
Author(s):  
Soon Hwa Jang ◽  
Seong Dae Kim ◽  
Jae-Kyoon Kim
Keyword(s):  
Difference Image ◽  
Coding Scheme ◽  
Frame Difference ◽  
Interframe Coding ◽  
Effective Representation

A FAST WAVELET-BASED VIDEO CODEC AND ITS APPLICATION IN AN IP VERSION 6-READY SERVERLESS VIDEOCONFERENCING SYSTEM

2004 ◽  
Vol 02 (02) ◽  
pp. 165-171 ◽  
Author(s):  
H. L. CYCON ◽  
M. PALKOW ◽  
T. C. SCHMIDT ◽  
M. WÄHLISCH ◽  
D. MARPE
Keyword(s):  
Video Conferencing ◽  
Video Codec ◽  
Global Network ◽  
Communication Framework ◽  
Coding Scheme ◽  
Frame Difference ◽  
Fast Wavelet ◽  
The One ◽  
Low Complex ◽  
Videoconferencing System

The purpose of this paper is twofold: On the one hand, we propose a fast wavelet-based video codec which is implemented into a real-time video conferencing tool. The proposed codec uses temporal frame difference coding, a computationally low-complex 5/3 tap wavelet transform, and a fast entropy coding scheme based on Golomb–Rice codes. On the other hand, we present an application of the video conferencing tool in a serverless peer-to-peer IP-based communication framework. For mobile communication we propose a simple, ready-to-use location scheme for video conference users in a global network.

Object Detection Based on the Frame Difference and Cellular Automata

2011 ◽  
Vol 328-330 ◽  
pp. 2229-2233
Author(s):  
Xiao Liang Feng ◽  
Xue Jun Xu
Keyword(s):  
Computer Vision ◽  
Cellular Automata ◽  
Object Detection ◽  
Video Surveillance ◽  
Moving Object ◽  
Accurate Information ◽  
Precise Result ◽  
Difference Image ◽  
Frame Difference ◽  
Accurate Detection

To give a relative accurate detection result in the computer vision which apply in the Video Surveillance and so on. A method based on the auto collects the seeds and then use the Cellular atuomata to subtract the moving object. Firstly we use the frame difference image to find the moving region and give the seeds of the foreground and background. Then we use the grow cut of CA to cut the frame into the foreground and background. The experiment is shown our seeds can give more accurate information of the foreground and get a relative precise result.

Improved Moving Target Detection Technology

2014 ◽  
Vol 971-973 ◽  
pp. 1628-1632 ◽  
Author(s):  
Xiao Hui Jin ◽  
Wei Yang ◽  
Qian Jin Liu ◽  
Di Zhao ◽  
Sheng Xu
Keyword(s):  
Difference Method ◽  
Background Subtraction ◽  
Detection System ◽  
Ccd Camera ◽  
Target Image ◽  
Target Region ◽  
Difference Image ◽  
Frame Difference ◽  
Detection Technology ◽  
The Difference

In order to detect target clearly, a detection system based on DM642 was designed. The system used improved frame-difference method combined with the background subtraction to detect target. First, the CCD camera scanned the surroundings step by step, then the background model was built, and improved three-frame-difference method was used to get the three-frame-difference image. The target image was the difference of target region extracted by three-frame-difference method and the target region extracted by background subtraction method. Experiments showed that the target image had less interference and a clear profile.

A Motion Image Detection Method Based on the Inter-Frame Difference Method

2014 ◽  
Vol 490-491 ◽  
pp. 1283-1286 ◽  
Author(s):  
Yuan Hang Cheng ◽  
Jing Wang
Keyword(s):  
Target Detection ◽  
Difference Method ◽  
Background Subtraction ◽  
Vision System ◽  
Robot Vision ◽  
Main Idea ◽  
Image Method ◽  
Detection Model ◽  
Difference Image ◽  
Frame Difference

Mobile robot vision system based on image information on environment, to make it automatic separation from obstacles and achieve precise mathematical description of obstacles, we construct detection model which combined by the frame difference method and background subtraction for target detection, comprehensive utilization of the main idea of three frame difference image method, the background subtraction and frame difference method combined to complement each other, thereby overcoming each other's weaknesses and improving the effect of target detection, experiment results show that this method can effectively improve the efficiency of target detection.

scholarly journals Moving Object Detection on CCTV Surveillance Using the Frame Difference Method

2019 ◽  
Vol 4 (2) ◽  
pp. 114-122
Author(s):  
Saluky Saluky
Keyword(s):  
Moving Objects ◽  
Simple Algorithm ◽  
Absolute Difference ◽  
Difference Image ◽  
Frame Difference ◽  
Morphological Filtering ◽  
The Difference ◽  
Cctv Surveillance ◽  
Build Systems ◽  
Static Background

In today's computer vision research, many build systems for observing humans and understanding their appearance, activities, and behaviour that provide sophisticated interfaces for interacting with humans, and create plausible human models for various purposes. This paper presents a simple algorithm for detecting moving objects from a static background based on frame differences. First, the first frame is captured via a static camera such as Closed Circuit Television (CCTV) after which a sequence of frames is taken periodically. Second, the absolute difference is calculated between successive frames and the difference in images is stored in the system. Third, the difference image is converted into a grey image and then translated into a binary image. Finally, morphological filtering is carried out to remove noise. In the last process, moving objects can be detected in conditions that do not change much apart from moving objects.

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