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TITLE PAGE
COLOR DETECTION USING PYTHON
BY
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--/H2013/01430
DEPARTMENT OF ----
SCHOOL OF ---
INSTITUTE OF ---
DECEMBER,2018
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This is to certify that the research work, "color detection using python" by ---, Reg. No. --/H2007/01430 submitted in partial fulfillment of the requirement award of a Higher National Diploma on --- has been approved.
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Supervisor Head of Department.
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DEDICATION
This project is dedicated to Almighty God for his protection, kindness, strength over my life throughout the period and also to my --- for his financial support and moral care towards me.Also to my mentor --- for her academic advice she often gives to me. May Almighty God shield them from the peril of this world and bless their entire endeavour Amen.
ACKNOWLEDGEMENT
The successful completion of this project work could not have been a reality without the encouragement of my --- and other people. My immensely appreciation goes to my humble and able supervisor mr. --- for his kindness in supervising this project.
My warmest gratitude goes to my parents for their moral, spiritual and financial support throughout my study in this institution.
My appreciation goes to some of my lecturers among whom are Mr. ---, and Dr. ---. I also recognize the support of some of the staff of --- among whom are: The General Manager, Deputy General manager, the internal Auditor Mr. --- and the ---. Finally, my appreciation goes to my elder sister ---, my lovely friends mercy ---, ---, --- and many others who were quite helpful.
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Color detection is necessary to recognize objects, it is also used as a tool in various image editing and drawing apps. I write a simple Python code to detect the color in the image using OpenCV. In the following work, we will be detecting contours, shapes and colors of various geometrical figures in the sample given binary images using Python 2.7, Open Source Computer Vision Library (OpenCV). The very fundamental functions are used for processing the images, that involves loading them, and detecting various shapes and colors inside the given sample images.
TABLE OF CONTENT
COVER PAGE
APPROVAL PAGE
DEDICATION
ACKNOWLEDGEMENT
TABLE OF CONTENT
- INTRODUCTION
- STATEMENT OF THE PROBLEM
- AIM AND OBJECTIVES OF THE STUDY
- SCOPE OF THE STUDY
- SIGNIFICANCE OF THE STUDY
- DEFINITION OF COLOR DETECTION
- RESEARCH QUESTION
- LIMITATION OF THE PROJECT
- DEFINITION OF TERMS
- PROJECT ORGANISATION
CHAPTER TWO
2.0 LITERATURE REVIW
2.1 REVIEW OF THE STUDY
2.2 REVIEW OF DIFFERENT TYPES OF COLOURS
CHAPTER THREE
3.0 METHODODLOGY
3.1 INTRODUCTION
3.2 PROGRAM DESCRIPTION
3.3 SYSTEM FLOW CHART
3.4 PYTHON VS OTHER PROGRAMMING LANGUAGES FOR COMPUTER VISION
3.5 STEPS FOR DETECTING COLOR IN AN IMAGE
CHAPTER FOUR
4.0 RESULT
4.1 PROGRAM CODE
4.2 APPLICATIONS AND FUTURE SCOPE
4.3 CHALLENGES
CHAPTER FIVE
5.1 CONCLUSION
5.2 REFERENCES
CHAPTER ONE
1.0 INTRODUCTION
1.1 BACKGROUND OF THE STUDY
Color detection is the process of detecting the name of any color. Simple isn’t it? Well, for humans this is an extremely easy task but for computers, it is not straightforward. Human eyes and brains work together to translate light into color. Light receptors that are present in our eyes transmit the signal to the brain. Our brain then recognizes the color.
Color recognition is the process of segmenting the colors and identifying the segmented colors. It is the one of the human to computer interaction. Here the colors are acting as interface between human and computer. At initial primary color modal is used for a recognition process, it only recognizing primary colors In the every color images, primary colors are segmented and segmented colors are recognized to identify its name like red, green, blue. It gives the recognized color as a output by using two ways, that is printing text on the output screen and playing audio(.wav) files which having the names of the primary colors. The pixels of every three colors are counted after segmented it. Whenever it gets above 300 pixels of these three colors (RGB) it should recognizes that the given colors are found. That we set that below 300 pixels are not any object found there. It may be a diffraction from light. So that it should not consider the colors below 300 pixels of the primary colors. Also the other colors are also neglected. These are the core process of color recognition. In the real time process, real time signals are processed by certain algorithms, for this project real time input signal is continuous motion of image signal i.e., video signal. It does not have any finite duration, algorithm monitoring for every frame and processing by the given algorithm.
In this color detection Python project, we are going to build an application through which you can automatically get the name of the color by clicking on them. So for this, we will have a data file that contains the color name and its values. Then we will calculate the distance from each color and find the shortest one.
1.2 PROBLEM STATEMENT
Detecting colours with our physical eyes is always difficult in the sense that some colours resemble one another. Also, Color vision deficiency is commonly known as color blind, is a type of vision defect in our eyeball. The inability to recognize color has caused several problems to the patient daily life and in conducting certain color oriented activities. Colour detecting system makes it easier and simple when detecting colours. This system was design in a way that it will automatically get the name of the color by clicking on them
1.3 OBJECTIVE OF THE STUDY
In this color detection Python project, the objective of this study is to build an application through which you can automatically get the name of the color by clicking on them.
1.4 SIGNIFICANCE OF THE STUDY
We will be working with colors and you will get to learn about many concepts throughout this project. Colour detection is necessary to recognize objects, it is also used as a tool in various image editing and drawing apps.
1.5 SCOPE OF THE STUDY
Colors are made up of 3 primary colors; red, green, and blue. In computers, we define each color value within a range of 0 to 255. So in how many ways we can define a color? The answer is 256*256*256 = 16,581,375. There are approximately 16.5 million different ways to represent a color. In our dataset, we need to map each color’s values with their corresponding names. But don’t worry, we don’t need to map all the values. We will be using a dataset that contains RGB values with their corresponding names.
In this work, we design and implement a color recognizer using Python. This process is also known as “Color Detection”. We will create a basic application that will help us to detect the colors in an image. The program will also return as the RGB values of the colors, which is really helpful. Many graphic designers and web designers will understand how RGB values can be helpful. Building a color recognizer is a great project to get started with Computer Vision.
1.6 DEFINITION OF COLOR DETECTION
Color detection is the process of detecting the name of any color. Simple isn’t it? Well, for humans this is an extremely easy task but for computers, it is not straightforward. Human eyes and brains work together to translate light into color. Light receptors that are present in our eyes transmit the signal to the brain. Our brain then recognizes the color.
1.7 RESEARCH QUESTION
- What is color detection?
- How can I find out the number of colors in an image?
- How do I identify a color in python?
- How do I find the color of an image in Python?
1.8 DEFINITION OF TERMS
Gray Conversion: It is the process of conversion from color images into gray scale image. Color image contains 24 bits per pixel; it is reduced into 8 bits per pixel. Most commonly gray levels represent the interval number of quantization in gray scale image processing. At present, the most commonly used storage method is 8-bit storage. There are 256 gray levels in an 8 bit gray scale image, and the intensity of each pixel can have from 0 to 255.
Subtraction: The RGB image contains 24 bits, each of three colour shaving 8 bits per pixel. At parallel RGB is splitting into each 8 bit colours.
The colour subtraction is the process of subtracting the colour values between the two colours. Here each three colours are subtracted with the gray image which converted from the original RGB image.
Binary Conversion: Binary conversion is the process of converting any kind of image into a binary image. Basically binary image two bits image, it contains only 0 and 1.Here 1 will be represented as white and 0 will be represented as black. Hence it’s called as black and white image. The purpose of conversion is to count the white and black pixels in the image. Each separated colouris converted as white and other colours are converted as black.
CHAPTER TWO: The chapter one of this work has been displayed above. The complete chapter two of "color detection using python" is also available. Order full work to download. Chapter two of "color detection using python" consists of the literature review. In this chapter all the related work on "color detection using python" was reviewed.
CHAPTER THREE: The complete chapter three of "color detection using python" is available. Order full work to download. Chapter three of "color detection using python" consists of the methodology. In this chapter all the method used in carrying out this work was discussed.
CHAPTER FOUR: The complete chapter four of "color detection using python" is available. Order full work to download. Chapter four of "color detection using python" consists of all the test conducted during the work and the result gotten after the whole work
CHAPTER FIVE: The complete chapter five of design and construction of a "color detection using python" is available. Order full work to download. Chapter five of "color detection using python" consist of conclusion, recommendation and references.
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