scholarly journals A FLEXIBLE IMAGE PROCESSING DESIGN BASED ON 2D DCT/IDCT FOR A SYSTEM ON A PROGRAMMABLE CHIP

2010 ◽  
pp. 315-319
Author(s):  
Mohamed Atri ◽  
Wajdi Elhamzi ◽  
Rached Tourki
Keyword(s):  
Image Processing ◽  
Object Recognition ◽  
Video Coding ◽  
Discrete Cosine Transform ◽  
Processing Time ◽  
Hardware Acceleration ◽  
Experimental Results ◽  
Software Implementation ◽  
Xilinx Fpga ◽  
Inverse Dct

Many multimedia applications require a flexible image pr ocessing architecture. In this paper, we present the use of a hardware acceleration module (Discrete Cosine Transform (DCT) and Inverse DCT (IDCT) coupled with a software partition running on a PowerPC Processor of a Xilinx FPGA. Therefore we have the benefits of flexible software partition on the PowerPC and the acceleration given by the remaining logic of the same FPGA. This implementation can be used in the context of video coding, object recognition, etc. The experimental results show optimization in processing time offered by hardware acceleration vs. software implementation.

scholarly journals Low Cost Design of a Hybrid Architecture of Integer Inverse DCT for H.264, VC-1, AVS, and HEVC

VLSI Design ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Muhammad Martuza ◽  
Khan A. Wahid
Keyword(s):  
Video Coding ◽  
Discrete Cosine Transform ◽  
Low Cost ◽  
Hybrid Architecture ◽  
Matrix Operation ◽  
Hardware Cost ◽  
Video Codecs ◽  
Symmetric Structure ◽  
Advanced Video Coding ◽  
Inverse Dct

The paper presents a unified hybrid architecture to compute the 8×8 integer inverse discrete cosine transform (IDCT) of multiple modern video codecs—AVS, H.264/AVC, VC-1, and HEVC (under development). Based on the symmetric structure of the matrices and the similarity in matrix operation, we develop a generalized “decompose and share” algorithm to compute the 8×8 IDCT. The algorithm is later applied to four video standards. The hardware-share approach ensures the maximum circuit reuse during the computation. The architecture is designed with only adders and shifters to reduce the hardware cost significantly. The design is implemented on FPGA and later synthesized in CMOS 0.18 um technology. The results meet the requirements of advanced video coding applications.

scholarly journals DESIGN ANALYSIS OF 2-D DWT BASED IMAGE COMPRESSION USING FPGA FOR MEMORY SPEED OPTIMIZER.

2020 ◽  
Vol 9 (7) ◽  
pp. 214-220
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Data Compression ◽  
Processing Time ◽  
Hardware Acceleration ◽  
Discrete Wavelet ◽  
Compression Performance ◽  
Pure Mathematics ◽  
Software Implementations ◽  
Good Compression

Wavelet Transform is successfully applied a number of fields, covering anything from pure mathematics to applied science. Numerous studies, done on wavelet Transform, have proven its advantages in image processing and data compression and have made it a encoding technique in recent data compression standards along with multi- resolution decomposition of signal and image processing applications. Pure software implementations for the Discrete Wavelet Transform (DWT), however, seem the performance bottleneck in realtime systems in terms of performance. Therefore, hardware acceleration for the DWT has developed into topic of contemporary research. On the compression of image using 2-Dimensional DWT (2D-DWT) two filters are widely-used, a highpass as well as a lowpass filter. Because filter coefficients are irrational numbers, it's advocated that they must be approximated with the use of binary fractions. The truth and efficiency with that your filter coefficients are rationalized within the implementation impacts the compression and critical hardware properties just like throughput and power consumption. An expensive precision representation ensures good compression performance, but at the expense of increased hardware resources and processing time. Conversely, lower precision with the filter coefficients ends up with smaller, faster hardware, but at the expense of poor compression performance.

Developing an Inkjet Printer I: RGB Image to CMY Ink Amounts - Image Processing and Color Management

2020 ◽  
Vol 2020 (15) ◽  
pp. 350-1-350-10
Author(s):  
Yin Wang ◽  
Baekdu Choi ◽  
Davi He ◽  
Zillion Lin ◽  
George Chiu ◽  
...  
Keyword(s):  
Image Processing ◽  
Low Cost ◽  
Experimental Results ◽  
Color Management ◽  
Finger Nail ◽  
Inkjet Printer ◽  
Rgb Image ◽  
Novel Algorithm

In this paper, we will introduce a novel low-cost, small size, portable nail printer. The usage of this system is to print any desired pattern on a finger nail in just a few minutes. The detailed pre-processing procedures will be described in this paper. These include image processing to find the correct printing zone, and color management to match the patterns’ color. In each phase, a novel algorithm will be introduced to refine the result. The paper will state the mathematical principles behind each phase, and show the experimental results, which illustrate the algorithms’ capabilities to handle the task.

scholarly journals OFCOD: On the Fly Clustering Based Outlier Detection Framework

Data ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ahmed Elmogy ◽  
Hamada Rizk ◽  
Amany M. Sarhan
Keyword(s):  
Data Mining ◽  
Image Processing ◽  
Intrusion Detection ◽  
Real Time ◽  
Outlier Detection ◽  
Real World ◽  
Medical Data ◽  
Experimental Results ◽  
Real Time Applications ◽  
Real World Datasets

In data mining, outlier detection is a major challenge as it has an important role in many applications such as medical data, image processing, fraud detection, intrusion detection, and so forth. An extensive variety of clustering based approaches have been developed to detect outliers. However they are by nature time consuming which restrict their utilization with real-time applications. Furthermore, outlier detection requests are handled one at a time, which means that each request is initiated individually with a particular set of parameters. In this paper, the first clustering based outlier detection framework, (On the Fly Clustering Based Outlier Detection (OFCOD)) is presented. OFCOD enables analysts to effectively find out outliers on time with request even within huge datasets. The proposed framework has been tested and evaluated using two real world datasets with different features and applications; one with 699 records, and another with five millions records. The experimental results show that the performance of the proposed framework outperforms other existing approaches while considering several evaluation metrics.

scholarly journals DV-DVFS: merging data variety and DVFS technique to manage the energy consumption of big data processing

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hossein Ahmadvand ◽  
Fouzhan Foroutan ◽  
Mahmood Fathy
Keyword(s):  
Big Data ◽  
Energy Consumption ◽  
Processing Time ◽  
Experimental Results ◽  
The Other ◽  
Data Sets ◽  
Multiple Sources ◽  
Evaluation Phase ◽  
Dynamic Voltage ◽  
Processing Resources

AbstractData variety is one of the most important features of Big Data. Data variety is the result of aggregating data from multiple sources and uneven distribution of data. This feature of Big Data causes high variation in the consumption of processing resources such as CPU consumption. This issue has been overlooked in previous works. To overcome the mentioned problem, in the present work, we used Dynamic Voltage and Frequency Scaling (DVFS) to reduce the energy consumption of computation. To this goal, we consider two types of deadlines as our constraint. Before applying the DVFS technique to computer nodes, we estimate the processing time and the frequency needed to meet the deadline. In the evaluation phase, we have used a set of data sets and applications. The experimental results show that our proposed approach surpasses the other scenarios in processing real datasets. Based on the experimental results in this paper, DV-DVFS can achieve up to 15% improvement in energy consumption.

scholarly journals Rotation Estimation: A Closed-Form Solution Using Spherical Moments

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4958
Author(s):  
Hicham Hadj-Abdelkader ◽  
Omar Tahri ◽  
Houssem-Eddine Benseddik
Keyword(s):  
Image Processing ◽  
Closed Form ◽  
Synthetic Data ◽  
Closed Form Solution ◽  
Form Solution ◽  
Unified Model ◽  
Experimental Results ◽  
Motion Information ◽  
Vision Sensors ◽  
Spherical Projection

Photometric moments are global descriptors of an image that can be used to recover motion information. This paper uses spherical photometric moments for a closed form estimation of 3D rotations from images. Since the used descriptors are global and not of the geometrical kind, they allow to avoid image processing as features extraction, matching, and tracking. The proposed scheme based on spherical projection can be used for the different vision sensors obeying the central unified model: conventional, fisheye, and catadioptric. Experimental results using both synthetic data and real images in different scenarios are provided to show the efficiency of the proposed method.

GPU processing for parallel image processing and real-time object recognition

2014 ◽  
Author(s):  
Kevin Vincent ◽  
Damien Nguyen ◽  
Brian Walker ◽  
Thomas Lu ◽  
Tien-Hsin Chao
Keyword(s):  
Image Processing ◽  
Object Recognition ◽  
Real Time ◽  
Parallel Image Processing ◽  
Parallel Image ◽  
Gpu Processing
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