Advances in image and data processing using VLSI design. Volume 1, Smart vision systems. / edited by Sandeep Saini [and three others].

Format:

Book

Contributor:

Saini, Sandeep, editor.

Series:

IOP Ebooks Series

Language:

English

Subjects (All):

Electronic data processing.

Punched card systems.

Physical Description:

1 online resource (282 pages)

Edition:

First edition.

Place of Publication:

Bristol, England : IOP Publishing, [2021]

Summary:

This book provides a framework for design, modeling concepts, and application of Image Processing based systems using VLSI design techniques. This volume focuses on a range of topics including object detection, recognition, smart traffic management and more, helping the research community to get in-depth knowledge of various systems that can be designed with image processing techniques using hardware.

Contents:

Intro

Preface

Acknowledgments

Editors&amp

#x02019

biographies

Sandeep Saini

Kusum Lata

Abhishek Sharma

G R Sinha

List of contributors

Chapter 1 An FPGA implementation of the RSA algorithm using VHDL and a Xilinx system generator for image applications

1.1 Introduction

1.2 Literature review

1.2.1 Introduction to cryptographic algorithms

1.2.2 Types of cryptographic algorithm

1.2.3 Important terminology

1.2.4 Comparison of different cryptographic algorithms

1.2.5 Comparison of the implementations of different cryptographic algorithms

1.3 Mathematical formulation

1.3.1 Bézout's theorem

1.3.2 The Euclidean algorithm

1.3.3 The extended Euclidean algorithm

1.3.4 Euler's totient function and Euler's theorem

1.3.5 Modular exponentiation techniques

1.3.6 Chinese remainder theorem

1.4 RSA system

1.4.1 Key generation

1.4.2 Encryption

1.4.3 Decryption

1.5 System implementation

1.5.1 Key generation

1.5.2 Encryption

1.5.3 Decryption

1.5.4 Area and throughput comparison with existing implementations

1.6 Implementation results for the SPARTAN-6 (XC6SLX45-CSG324) FPGA board

1.6.1 Design of the SPARTAN-6 (XC6SLX45-CSG324) FPGA board

1.6.2 Implementation of key security for the AES algorithm using RSA (hybrid cryptosystem)

1.7 Conclusions

Bibliography

Chapter 2 Modern ML methods for object detection

2.1 Introduction

2.2 Machine-learning overview

2.3 Computer vision algorithms

2.3.1 Image classification

2.3.2 Object detection

2.3.3 Segmentation of images

2.3.4 You Only Look Once (YOLO)

2.3.5 Faster region-based convolutional neural networks

2.3.6 Support vector machine (SVM)

2.3.7 Systolic array architectures

2.3.8 Mask R-CNN

2.4 Hardware implementation

2.5 Conclusions.

Bibliography and further reading

Chapter 3 Embedded intelligence for tracking facial expressions

3.1 Introduction

3.2 Description of algorithm

3.3 Implementation

3.3.1 OpenCV with three simple Haar Cascades

3.3.2 DLib

3.3.3 OpenCV and DLib

3.3.4 Mitigating loss of track

3.4 Results and evaluation

3.5 Conclusions

Chapter 4 The roles of delay and power optimization techniques in VLSI design

4.1 Delay optimization

4.2 Area optimization

4.3 Variable input delay

4.3.1 The concept of the variable input delay technique

4.4 System implementation

4.4.1 D flip-flop

4.4.2 Full adder circuit

4.5 Digital Logic Design and Implementation

4.5.1 Architectural design of the work

4.6 Hardware/software used for experiments

4.6.1 Introduction to the ISE design suite

4.6.2 Features of the Spartan 3E

4.7 Experimental results and analysis

4.7.1 Experimental variations

4.7.2 Experimental details

4.8 Results

4.8.1 Simulation results for the full adder

4.9 Comparative analysis of results

4.10 Comparison of results

4.11 Conclusions

Bibliography and further reading

Chapter 5 SIVAS: smart interactive virtual assistance system-a voice user interface

5.1 Introduction

5.1.1 Aim

5.1.2 Objectives

5.1.3 Challenges

5.1.4 Use cases

5.2 Literature review

5.3 Methodology

5.3.1 Initialization

5.3.2 Input unit

5.3.3 Processing unit

5.3.4 Retrieval unit

5.3.5 Output unit

5.4 Functionalities

5.4.1 Command mode

5.4.2 Cursor mode

5.5 Hardware implementation

5.5.1 Introduction

5.5.2 Required devices

5.6 Experimental results

5.7 Limitations and future work

5.8 Result and conclusions

Appendix A

Further reading.

Chapter 6 A topical survey of computing solutions for plant disease classification using deep learning techniques

6.1 Introduction

6.2 Related work

6.3 Algorithmic survey

6.3.1 LeNet-5 [17, 18]

6.3.2 Convolutional neural network-long short-term network (CNN-LSTM) [19]

6.3.3 AlexNet [20, 21]

6.3.4 ResNet [22]

6.4 Comparative study for performance analysis

6.5 Common findings and challenges

6.5.1 Common findings

6.5.2 Challenges

6.6 Hardware implementations

6.7 Conclusions

Chapter 7 Hardware IP cores for image processing functions

7.1 Introduction

7.2 HLS methodology used to design IP cores for image processing functions

7.2.1 Generalization of convolution for image processing functions

7.2.2 Application-specific reusable IP cores for image processing functions

7.3 Case studies and analysis

7.3.1 Gate-count analysis

7.3.2 Power analysis

7.4 Conclusions

Acknowledgements

Chapter 8 An efficient underwater image cryptosystem that uses a novel hybrid algorithm

8.1 Introduction

8.2 Dynamic histogram enhancement technique

8.3 Improved secure force algorithm for underwater image transmission

8.3.1 Key-generation block

8.3.2 Key management block

8.3.3 Encryption block

8.4 Evaluation parameters used for the hybrid underwater image cryptosystem

8.4.1 Peak signal-to-noise ratio and mean squared error

8.4.2 Mean absolute error

8.4.3 Horizontal and vertical correlations

8.4.4 Number of pixels change rate (NPCR) and unified average change intensity (UACI)

8.4.5 Encryption and decryption times

8.5 Results and discussion

8.6 Conclusions

Chapter 9 A survey of thresholding in image processing

9.1 Introduction

9.2 Histogram-based methods

9.2.1 Balanced-histogram-based thresholding.

9.3 Clustering-based methods

9.3.1 Iterative clustering

9.3.2 Clustering thresholding

9.3.3 Minimum-error thresholding

9.3.4 Fuzzy clustering thresholding

9.3.5 k-means clustering thresholding

9.4 Entropy-based thresholding

9.4.1 Cross-entropy thresholding

9.4.2 Fuzzy entropy thresholding

9.5 Attribute similarity methods

9.6 Local method

9.7 Conclusions

Chapter 10 Review of quality assessment of fruit and vegetables using NIR spectroscopy

10.1 Introduction

10.2 NIR spectroscopy

10.2.1 NIR spectrometer

10.2.2 Modes of data acquisition in NIR spectroscopy systems

10.3 Chemometrics

10.3.1 Preprocessing methods

10.4 Calibration methods

10.4.1 Multiple linear regression (MLR)

10.4.2 Principal component regression (PCR)

10.4.3 Partial least-squares regression (PLS)

10.4.4 Least-squares support vector machine (LS-SVM)

10.4.5 Artificial neural network (ANN)

10.5 DLP technology in near-infrared (NIR) spectroscopy

10.5.1 Proposed fruit and vegetable quality detection system

10.6 Fruit and vegetable quality parameters

10.6.1 Soluble solid content (SSC)

10.6.2 Sugar content

10.6.3 Firmness

10.6.4 Dry matter

10.6.5 Titratable acidity

10.6.6 Carotenoid content

10.7 Discussion

10.8 Conclusions

Chapter 11 Design and implementation of processors for secure image processing applications

11.1 Introduction

11.2 Literature survey

11.3 Vedic mathematics

11.3.1 Vedic sutras

11.3.2 Urdhva tiryagbhyam

11.3.3 Paravartya

11.4 Proposed system design and architecture

11.4.1 Design overview

11.4.2 Fundamental building blocks

11.4.3 Instruction set architecture

11.4.4 Software specification and design flow

11.5 Simulation results

11.5.1 Integrated circuit design.

11.5.2 Compiler design

11.5.3 Performance analysis

11.6 Applications

11.7 Results and conclusions

Chapter 12 Low-power modified phase-locked loop using AVLS technique for biomedical applications

12.1 Introduction

12.2 Literature review

12.3 Design and implementation of a modified PLL

12.3.1 Phase detector

12.3.2 Charge pump, loop filter, and current-starved VCO

12.3.3 AVLS approach

12.3.4 Proposed modified PLL

12.4 Results and discussion

12.5 Conclusions

Chapter 13 Image multiplication with a power-efficient approximate multiplier using a 4:2 compressor

13.1 Introduction

13.2 Existing 4:2 compressor

13.3 Proposed work

13.4 Results and discussion

13.4.1 Simulations of 4:2 compressors and multipliers

13.4.2 Error analysis

13.4.3 Image multiplication

13.5 Conclusions

Chapter 14 A comparison of different procedures for hardware-based video shot boundary detection

14.1 Introduction

14.2 Literature review

14.3 Methodology

14.3.1 Comparative discussion of results

14.3.2 Hardware implementation

14.4 Conclusions

Chapter 15 Hardware-software co-simulation of vehicle license plate detection on the ZedBoard SoC platform

15.1 Introduction

15.1.1 Literature survey

15.1.2 Contributions and organization

15.2 Descriptions of algorithms

15.2.1 Edge-based extraction

15.2.2 Connected-component-based extraction

15.2.3 Histogram-based edge processing

15.3 Comparative results

15.4 Hardware-software co-simulation of automatic license plate detection on the ZedBoard SoC platform

15.4.1 Simulink model

15.4.2 System generator model

15.5 Results and utilization summary

15.5.1 Resource utilization summary.

15.6 Conclusions and future work.

Notes:

Description based on publisher supplied metadata and other sources.

Description based on print version record.

Includes bibliographical references.

ISBN:

9780750345835

0750345837

OCLC:

1429734909