scholarly journals Multimedia Image Processing Lab Experiment/Simulation

2020 ◽  
Vol 3 (1) ◽  
pp. 1-13
Author(s):  
Md Mamunur Rashid
Keyword(s):  
Image Processing ◽  
Video Compression ◽  
Video Processing ◽  
Multimedia Systems ◽  
Multimedia System ◽  
Image And Video Processing ◽  
Indexing And Retrieval ◽  
Video Indexing And Retrieval ◽  
Multimedia Image ◽  
Processing Techniques

Image Processing in Multimedia Applications treats a number of critical topics in multimedia systems, with respect to image and video processing techniques and their implementations. These techniques include the Image and video compression techniques and standards, and Image and video indexing and retrieval techniques. Image Processing is an important tool to develop a Multimedia system design.

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

scholarly journals An Efficient Design of DCT Approximation Based on Quantum Dot Cellular Automata (QCA) Technology

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Ismail Gassoumi ◽  
Lamjed Touil ◽  
Bouraoui Ouni ◽  
Abdellatif Mtibaa
Keyword(s):  
Image Processing ◽  
Cellular Automata ◽  
Quantum Dot ◽  
Low Power ◽  
Video Compression ◽  
Video Processing ◽  
Power Dissipation ◽  
Functional Verification ◽  
Efficient Design ◽  
Quantum Dot Cellular Automata

Optimization for power is one of the most important design objectives in modern digital image processing applications. The DCT is considered to be one of the most essential techniques in image and video compression systems, and consequently a number of extensive works had been carried out by researchers on the power optimization. On the other hand, quantum-dot cellular automata (QCA) can present a novel opportunity for the design of highly parallel architectures and algorithms for improving the performance of image and video processing systems. Furthermore, it has considerable advantages in comparison with CMOS technology, such as extremely low power dissipation, high operating frequency, and a small size. Therefore, in this study, the authors propose a multiplier-less DCT architecture in QCA technology. The proposed design provides high circuit performance, very low power consumption, and very low dimension outperform to the existing conventional structures. The QCADesigner tool has been utilized for QCA circuit design and functional verification of all designs in this work. QCAPro, a very widespread power estimator tool, is applied to estimate the power dissipation of the proposed circuit. The suggested design has 53% improvement in terms of power over the conventional solution. The outcome of this work can clearly open up a new window of opportunity for low power image processing systems.

scholarly journals Performance Evaluation of Digital Image Processing by Using Scilab

2021 ◽  
Vol 9 (2) ◽  
pp. 239
Author(s):  
Rudi Heriansyah ◽  
Wahyu Mulyo Utomo
Keyword(s):  
Image Processing ◽  
Video Processing ◽  
Streaming Video ◽  
Grayscale Image ◽  
Video File ◽  
Computational Environment ◽  
Image And Video Processing ◽  
Cross Platform ◽  
The Difference ◽  
Rgb Image

Scilab is an open-source, cross-platform computational environment software available for academic and research purposes as a free of charge alternative to the matured computational copyrighted software such as MATLAB. One of important library available for Scilab is image processing toolbox dedicated solely for image and video processing. There are three major toolboxes for this purpose: Scilab image processing toolbox (SIP), Scilab image and video processing toolbox (SIVP) and recently image processing design toolbox (IPD). The target discussion in this paper is SIVP due to its vast use out there and its capability to handle streaming video file as well (note that IPD also supports video processing). Highlight on the difference between SIVP and IPD will also be discussed. From testing, it is found that in term of looping test, Octave and FreeMat are faster than Scilab. However, when converting RGB image to grayscale image, Scilab outperform Octave and FreeMat.

Methods and Perspectives in Face Tracking Based on Human Perception

2014 ◽  
pp. 289-315
Author(s):  
Vittoria Bruni ◽  
Domenico Vitulano
Keyword(s):  
Image Processing ◽  
Face Perception ◽  
Video Processing ◽  
Human Perception ◽  
Face Tracking ◽  
Early Vision ◽  
Image And Video Processing ◽  
Change Of Perspective ◽  
Face Detection And Recognition

This chapter aims at analyzing the role of human early vision in image and video processing, with particular reference to face perception, recognition, and tracking. To this aim, the change of perspective in approaching image processing-based problems where the decoder (human eye) plays a central role is analysed and discussed. In particular, the main topics of this contribution are some important neurological results that have been successfully used in face detection and recognition, as well as those that seem to be promising in giving new and powerful tools for face tracking, which remains a less investigated topic from this new standpoint.

Application of DWT in Intra-Frame Coding of Video Compression

2013 ◽  
Vol 380-384 ◽  
pp. 3710-3713
Author(s):  
Xiao Chen Jiang ◽  
Guo Ping Li ◽  
Hai Wu Zhao ◽  
Guo Zhong Wang
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Video Compression ◽  
Video Processing ◽  
Discrete Wavelet ◽  
Visual Effects ◽  
Compression Efficiency ◽  
Coding Efficiency ◽  
Image And Video Processing

With the development of modern signal processing technology, the method of Wavelet Transform (WT) has been greatly used in image and video processing. In this paper, a method to use Discrete Wavelet Transform (DWT) in intra-frame (I-frame) video compression is proposed for the purpose of better compression efficiency and quality on the basis of good visual effects. The method can be functioned as a preprocessing of I-frame coding. The experimental results show that the proposed method has an increase in both coding efficiency and quality.

A Comparative Study of Color Space Conversion on Homogeneous and Heterogeneous Multicore

2014 ◽  
Vol 519-520 ◽  
pp. 724-728
Author(s):  
Chen Chu ◽  
Jian Wang ◽  
Sen Ke Hou ◽  
Qi Lv ◽  
Guo Qiang Ma ◽  
...  
Keyword(s):  
Video Compression ◽  
Video Processing ◽  
Processing Time ◽  
Multicore Processors ◽  
Color Space ◽  
Data Parallelism ◽  
Heterogeneous Multicore ◽  
Color Space Conversion ◽  
Image And Video Processing ◽  
Novel Approaches

Color space conversion (CSC) is an important kernel in the area of image and video processing applications including video compression. As a matrix math, this operation consumes up to 40% of processing time of a highly optimized decoder. Therefore, techniques which efficiently implement this conversion are desired. Multicore processors provide an opportunity to increase the performance of CSC by exploiting data parallelism. In this paper, we present three novel approaches for efficient implementation of color space conversion suitable for homogeneous and heterogeneous multicore. We compare the performance of color space conversion on a variety of platforms including OpenMP running on homogeneous multicore CPUs, CUDA with NVIDIA GPUs and OpenCL running on both NVIDIA and ATI GPUs. Our experimental results show that the speedup of3×, 17×and15×can been obtained, respectively.

scholarly journals Real-Time Video Image Processing based on Kerr Soliton Krystal Microcombs

2021 ◽  
Author(s):  
mengxi tan ◽  
xingyuan xu ◽  
David Moss
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Video Processing ◽  
High Speed ◽  
Autonomous Driving ◽  
Next Generation ◽  
Video Signals ◽  
Image And Video Processing ◽  
Massively Parallel Processing ◽  
Photonic Processing

Advanced image processing will be crucial for emerging technologies such as autonomous driving, where the requirement to quickly recognize and classify objects under rapidly changing, poor visibility environments in real time will be needed. Photonic technologies will be key for next-generation signal and information processing, due to their wide bandwidths of 10’s of Terahertz and versatility. Here, we demonstrate broadband real time analog image and video processing with an ultrahigh bandwidth photonic processor that is highly versatile and reconfigurable. It is capable of massively parallel processing over 10,000 video signals simultaneously in real time, performing key functions needed for object recognition, such as edge enhancement and detection. Our system, based on a soliton crystal Kerr optical micro-comb with a 49GHz spacing with >90 wavelengths in the C-band, is highly versatile, performing different functions without changing the physical hardware. These results highlight the potential for photonic processing based on Kerr microcombs for chip-scale fully programmable high-speed real time video processing for next generation technologies.

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