Study and implementation of K-multiple constraint shortest path for H.265 HEVC for optimal video compression

2021 ◽  
Author(s):  
Rajender Kumar ◽  
Krishan Kumar ◽  
Shubham Mahajan ◽  
Amit Kant Pandit
Keyword(s):  
Video Compression ◽  
Shortest Path ◽  
Multiple Constraint

Modern Technology for Image processing and Computer vision -A Review

2018 ◽  
Vol 1 (2) ◽  
pp. 17-23
Author(s):  
Takialddin Al Smadi
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Augmented Reality ◽  
Video Compression ◽  
Video Processing ◽  
Vision System ◽  
Citrus Fruit ◽  
Modern Technology ◽  
Image And Video Processing ◽  
Depth Video

This survey outlines the use of computer vision in Image and video processing in multidisciplinary applications; either in academia or industry, which are active in this field.The scope of this paper covers the theoretical and practical aspects in image and video processing in addition of computer vision, from essential research to evolution of application.In this paper a various subjects of image processing and computer vision will be demonstrated ,these subjects are spanned from the evolution of mobile augmented reality (MAR) applications, to augmented reality under 3D modeling and real time depth imaging, video processing algorithms will be discussed to get higher depth video compression, beside that in the field of mobile platform an automatic computer vision system for citrus fruit has been implemented ,where the Bayesian classification with Boundary Growing to detect the text in the video scene. Also the paper illustrates the usability of the handed interactive method to the portable projector based on augmented reality.   © 2018 JASET, International Scholars and Researchers Association

Effect of Social Norm on Consumer Demand: Multiple Constraint Approach

2020 ◽  
Vol 22 (1) ◽  
pp. 41-60
Author(s):  
Sungjee Choi ◽  
Inwoo Nam ◽  
Jaehwan Kim
Keyword(s):  
Social Norm ◽  
Consumer Demand ◽  
Multiple Constraint ◽  
Constraint Approach

An Improved Method to CABAC in the H.264/AVC Video Compression Standard

2009 ◽  
Vol E92-A (12) ◽  
pp. 3355-3360
Author(s):  
LeThanh HA ◽  
Chun-Su PARK ◽  
Seung-Won JUNG ◽  
Sung-Jea KO
Keyword(s):  
Video Compression ◽  
Improved Method

Temporal Drift Correction of Residues for Perceptually Based Video Compression

2016 ◽  
Vol 2016 (1) ◽  
pp. 27-31
Author(s):  
MarkQ. Shaw ◽  
JanP. Allebach ◽  
EdwardJ. Delp
Keyword(s):  
Video Compression ◽  
Drift Correction

The Map-Based Shortest Route Selection by Using Ant Colony Optimization Algorithm

2018 ◽  
Vol 1 (1) ◽  
pp. 15
Author(s):  
Achmad Fanany Onnilita Gaffar ◽  
Agusma Wajiansyah ◽  
Supriadi Supriadi
Keyword(s):  
Ant Colony Optimization ◽  
Shortest Path ◽  
Optimization Algorithm ◽  
Optimization Problems ◽  
Google Earth ◽  
Ant Colony ◽  
Food Sources ◽  
Shortest Route ◽  
Study Results ◽  
Destination Point

The shortest path problem is one of the optimization problems where the optimization value is a distance. In general, solving the problem of the shortest route search can be done using two methods, namely conventional methods and heuristic methods. The Ant Colony Optimization (ACO) is the one of the optimization algorithm based on heuristic method. ACO is adopted from the behavior of ant colonies which naturally able to find the shortest route on the way from the nest to the food sources. In this study, ACO is used to determine the shortest route from Bumi Senyiur Hotel (origin point) to East Kalimantan Governor's Office (destination point). The selection of the origin and destination points is based on a large number of possible major roads connecting the two points. The data source used is the base map of Samarinda City which is cropped on certain coordinates by using Google Earth app which covers the origin and destination points selected. The data pre-processing is performed on the base map image of the acquisition results to obtain its numerical data. ACO is implemented on the data to obtain the shortest path from the origin and destination point that has been determined. From the study results obtained that the number of ants that have been used has an effect on the increase of possible solutions to optimal. The number of tours effect on the number of pheromones that are left on each edge passed ant. With the global pheromone update on each tour then there is a possibility that the path that has passed the ant will run out of pheromone at the end of the tour. This causes the possibility of inconsistent results when using the number of ants smaller than the number of tours.

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