A PERFORMANCE ANALYSIS OF STEREO MATCHING ALGORITHMS FOR STEREO VISION APPLICATIONS IN SMART ENVIRONMENTS

2020 ◽  
Vol 16 (1) ◽  
pp. 1
Author(s):  
Kavitha V ◽  
Balakrishnan G
Keyword(s):  
Performance Analysis ◽  
Stereo Vision ◽  
Stereo Matching ◽  
Smart Environments ◽  
A Performance

Comparison of QoS Performance Over WLAN, VoIP4 and VoIP6

2015 ◽  
Vol 2 (11) ◽  
pp. 42
Author(s):  
Esra Musbah Mohammed Musbah ◽  
Khalid Hamed Bilal ◽  
Amin Babiker A. Nabi Mustafa
Keyword(s):  
Performance Analysis ◽  
Internet Protocol ◽  
Voice Over Internet Protocol ◽  
Ip Network ◽  
Qos Parameters ◽  
Software Program ◽  
Jitter Delay ◽  
Qos Performance ◽  
Delay Variation ◽  
A Performance

VoIP stands for voice over internet protocol. It is one of the most widely used technologies. It enables users to send and transmit media over IP network. The transition from IPv4 to IPv6 provides many benefits for internet IPv6 is more efficient than IPv4. This paper presents a performance analysis of VoIP over WLAN using IPv4 and IPv6 and OPNET software program to simulate the protocols and to investigate the QoS parameters such as jitter, delay variation, packet send, and packet received and throughputs for IP4 and IP6 and compare between them.

scholarly journals High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo Vision

2021 ◽  
Vol 10 (4) ◽  
pp. 234
Author(s):  
Jing Ding ◽  
Zhigang Yan ◽  
Xuchen We
Keyword(s):  
Stereo Vision ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Target Localization ◽  
Parallel Structure ◽  
Moving Target ◽  
Target Area ◽  
Moving Targets ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

To obtain effective indoor moving target localization, a reliable and stable moving target localization method based on binocular stereo vision is proposed in this paper. A moving target recognition extraction algorithm, which integrates displacement pyramid Horn–Schunck (HS) optical flow, Delaunay triangulation and Otsu threshold segmentation, is presented to separate a moving target from a complex background, called the Otsu Delaunay HS (O-DHS) method. Additionally, a stereo matching algorithm based on deep matching and stereo vision is presented to obtain dense stereo matching points pairs, called stereo deep matching (S-DM). The stereo matching point pairs of the moving target were extracted with the moving target area and stereo deep matching point pairs, then the three dimensional coordinates of the points in the moving target area were reconstructed according to the principle of binocular vision’s parallel structure. Finally, the moving target was located by the centroid method. The experimental results showed that this method can better resist image noise and repeated texture, can effectively detect and separate moving targets, and can match stereo image points in repeated textured areas more accurately and stability. This method can effectively improve the effectiveness, accuracy and robustness of three-dimensional moving target coordinates.

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