Image Recognition and Enhancement using Multi-Scale Retinex and Histogram Equalization

Project Code :TMMAAI243

Objective

The objective of this project is to develop a system for image recognition and enhancement using Multi-Scale Retinex (MSR) and histogram equalization techniques. The proposed system aims to improve the visual quality and feature recognition of images by removing the effect of illumination and improving contrast.

Abstract

This project proposes a method for different objects detection based on the image recognition and enhancement using multi-scale retinex and histogram equalization with yolov2 object detector using images. first, we design the system for enhancing the image using multi-scale retinex and histogram equalization and from that final enhanced image object identification and detection. We are constructing which is mainly used to identify Human, Car, Tree, Airplane, Ship. In this work, detection of objects is implemented using YOLOv2 detector network. Although many automated detection approaches including those based on image processing techniques have been proposed, the detection performance still has room for improvement due to the large variability in image appearance. 

Keywords: multi-scale retinex, histogram equalization, Image Processing, Object detection, YOLOV2, MATLAB.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

Software: Matlab 2018a or above

Hardware:

Operating Systems:

·   Windows 10

·   Windows 7 Service Pack 1

·   Windows Server 2019

·    Windows Server 2016

Processors:

Minimum: Any Intel or AMD x86-64 processor

Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support

Disk:

Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation

Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space

RAM:

Minimum: 4 GB

Recommended: 8 GB

Learning Outcomes

·  Introduction to Matlab

·  What is EISPACK & LINPACK

·  How to start with MATLAB

·  About Matlab language

·  Matlab coding skills

·  About tools & libraries

·  Application Program Interface in Matlab

·  About Matlab desktop

·  How to use Matlab editor to create M-Files

·  Features of Matlab

·  Basics on Matlab

·  What is an Image/pixel?

·  About image formats

·  Introduction to Image Processing

·  How digital image is formed

·  Importing the image via image acquisition tools

·  Analyzing and manipulation of image.

·  Phases of image processing:

           o  Acquisition

            Image enhancement

            Image restoration

           o  Color image processing

           o  Image compression

            Morphological processing

             Segmentation etc.,

· How to extend our work to another real time applications

· Project development Skills

           o   Problem analyzing skills

           o   Problem solving skills

           o   Creativity and imaginary skills

           o   Programming skills

           o   Deployment

           o   Testing skills

           o   Debugging skills

           o   Project presentation skills

           o   Thesis writing skills

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