Department of Physics and Electronics

CHRIST (DEEMED TO BE UNIVERSITY)

Certificate

This is to certify that this is a bonafide record of the project presented by the Chirag N during the academic year 2022-23 in fulfilment of the requirements of the degree of Bachelor of Science in Physics, Mathematics and Electronics.

Chirag N(Signature of Student)

Dr. Vineeth V(Faculty in Charge)

Dr. Manoj B(Head of Department)

Date: 19 September 2022

Abstract : To plot an Image signal and to process the signal using image processing functions in Python.

Introduction

This document is a report on signal processing in Python. An image signal has been taken for reference and is processed into different versions of it. Image processing is a method to perform some operation on an image, in order to get an enhanced image or to extract some useful information from it. It is a type of signal processing in which input is an image and output maybe image or characteristics/features associated with that image.

Objectives

1. Reading in images

2. Image Array

3. Display images

4. Image Channels

5. Image Manipulation

6. Resizing and Scaling

7. Blurred image

Theory

Signal Processing is at the heart of our modern digital world. To perform a wide variety of signal processing operations, we use Digital Signal Processing. It is a sequence of numbers that represent samples of a continuous variable in a domain such as time, space, or frequency. Images are stored in form of a matrix of numbers in a computer where these numbers are known as pixel values. The pixel value represent intensity of signal, 0 being black and 255 being white.

Image processing is the technique to convert an image into digital format and perform operations on it to get an enhanced image or extract some useful information from it. Changes that take place in images are usually performed automatically and rely on carefully designed algorithms.

Flowchart

Methodology

1. Import the image library from Kaggle notebook.

2. Import matplotlib.pylab and cv2 libraries in the Kaggle notebook.

3. Image is read using img_mpl for mathplot.pylab library and img_cv2 for cv2 library.

4. Grey image is generated using img_gray.

5. Hence, the grey image is formed.

Result

Conclusion

The image is processed using function in Python. The img_mpl and img_cv2 libraries coverts RBG and BGR image to grey image converting all the white pixels black and black pixels white. Image processing is very useful in finding out various patterns and aspects of image. It’s useful in Medical Field, remote sensing, pattern recognition etc