Top 14 Image Processing Projects Using Python [2024]

Every image tells a unique story, harboring a wealth of information within its visual components. The data within these images holds immense value across various domains.  

 Leveraging Image Processing techniques in Python, you can delve into projects that extract and decode this valuable information. These endeavors serve as the backbone of computer vision, playing a crucial role in practical applications like self-driving cars, acrobatics, and deep learning-based object detection.  

With each project that I have listed here, you can deepen your understanding of this dynamic field, constantly refining your skills to interpret the stories embedded within every pixel better. Read further to find out! 

Image Processing Projects

Image processing is gaining much popularity in the tech industry because of its integration into various autonomous services. So, if you are a Python beginner, the best thing you can do is work on some real-time image processing projects. A digital image can be represented as a collection of pixels. The pixel is the smallest unit of an image. These pixel values contain the corresponding RGB (Red, Green, Blue) values that represent the proportion of colour contribution to the image, and a mixture of these build up an image. 

This field finds its application in almost every domain such as education, scientific and medical studies, traffic control, and government services. The image processing is most preferably done using deep learning as the image data is available in huge numbers and as the image is a matrix of numbers, it is easy to pass it to several layers of neurons and extract the important features from the image. These features help in deciding the action to be taken if this system is integrated into an application. The more you experiment with different image processing projects, the more knowledge you gain.

In this article, we will be exploring some interesting image processing projects which beginners can work on to put their knowledge to test. In this article, you will find top image processing project ideas for beginners to get hands-on experience on Python. 

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Image Processing Projects Using Python

Here we present you a list of 14 Image processing projects that can be built using Python and with which you can kick-start your journey to explore and add a new skill to your CV. These projects are not ranked in any order of difficulty and require you to understand Numpy which is the numerical computing library, OpenCV that allows you to process these images, CNN (Convolution Neural network) for extracting the features, and other project-specific libraries. 

1. Image-Based Attendance System

One of the best ideas to start experimenting you hands-on image processing projects is working on Image-based attendance system. As the educational institutes are adopting new technologies every single day, the attendance system in most institutions is still fingerprint or facial biometrics, but during this coronavirus situation, a contactless attendance system can be implemented using image processing.

The faculty member would simply take a group photograph of the class and after uploading that image to the cloud system, the attendance for the students will be marked. This makes the system fully digital and contactless. However, a student database for verification, storage for images, and other requirements will be required, but you can test out this project on a small scale. 

2. Live Air Games 

This project will make use of OpenCV and Python Pygame module. The Pygame module is a 2-D game development engine in Python that offers various tools for I/O and other functionalities. The player’s instructions can be captured via the webcam in the designated regions of the screens. Live Air games are one of the best image processing projects. 

Instructions include moving left, right, jumping, or grasping something. The live camera feed needs to be broken down into frames and then matching them with the instruction database for moving the player. You can implement this either on an existing game like Hill climb racing or create a new one for this!

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3. Smart Traffic Lights System

We all know that while travelling by roads, the traffic lights stoppage can annoy when the traffic is minimal or not at all, even so, we have to wait for the green signal to avoid any police disruption. What could be implemented is a smart lights system that analyses the traffic situation and accordingly adjusts the timing of the lights?

The live image feed can help in deciding the density of traffic and if horn sounds are also taken into consideration, a robust system could be developed. The system should give frequent green signals when the traffic density is low and more controlled flow when there is heavy congestion. A bias for emergency vehicles could also be added, allowing them to go through signals faster. 

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4. Snapchat Filters

Ever used Snapchat? In a nutshell, it is a popular messaging app that majorly focuses on photos and video sharing. This app offers various filters that allow users to create funny and theme-specific photos. These filters use the point face detection algorithms (for example, Haar-like feature) to structure out the important facial landmarks from the image and apply the custom filters or effects on them. This is one of the simple image processing projects yet an exciting one.

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You can take up the algorithm for points face detection and apply your work to them. This project will have the tech stack of Numpy, OpenCV, pillow and if you want to implement your own facial landmarks algorithm, then you can try that with the dlib library for Python.

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5. Image Classifier for Similar Types

A user may end up downloading a lot of images in their local machine and it gets filled up quickly. You could come up with a classifying system that puts the images in separate folders depending upon the category of the images. Similar images can be placed in one folder and blurred or distorted images in a separate folder. The images need to be analyzed for similarities.

Mentioning image processing projects can help your resume look much more interesting than others.

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6. Air Pollution Checker

Today most of us have been suffering from the pollution crisis. You can easily spot the difference between a cloudy or polluted environment just by looking at the sky, and this can be the main driving source of this project. The input for the application would be the image from the user via their mobile application or web portal depending upon the deployment, and after processing them, the result would be displayed on the screen. This is one of the excellent image processing projects for beginners.

For this project, you will need a huge dataset of cloudy, polluted, and clear sky images. Some of it is available on Kaggle, which is the Hub for data science and machine learning datasets, and some of them you can create of your own! 

Check out all trending Python tutorial concepts in 2024

7. Anti-Cheat System

Due to the covid situation, most of the University exams are being conducted via the online mode. It becomes difficult for the teachers/faculty to monitor the status of the students. An anti-cheat system can be developed that can detect if any unfair practice is performed by a candidate.

The system should be able to detect any outgoing navigation from the test screen. The candidate not looking at the screen for more time should be warned about the same and if the same activity is repeated several times, then it should be reported to the authorities to take the necessary action. 

8. Bonus Project: Image Editor

You can build up an image editor all using Python! The GUI for this can be made using Tkinter which is a Python GUI package. All the operations such as edit, crop, colour change, background blur, image merging, rotating, resizing, or dragging can be customized using Numpy and OpenCV. This project can take much time to create functions for all the required operations, but it will give you a good knowledge of image processing. 

9.Facial Mask Detection using Semantic Segmentation 

Growing interest in Image processing projects using Python with source code is quite natural; extracting facial masks and applying semantic segmentation for instance is one of the most famous applications. The technique of semantic segmentation which is used for each pixel labeling becomes a central concept in detecting masked and unmasked areas in faces. For those keen on diving into the technical details, I recommend checking out the source code provided in this GitHub repository, Facial mask detection using semantic segmentation 

 The projects highlight not only the power of Python in image processing but also its relevance in the real world like implementation in public spaces and healthcare facilities to enforce mask-wearing policies. With semantic segmentation integrated into image processing projects we can provide support for public health programs and safety procedures in preventing the spread of infectious diseases. 

10.Human Activity Recognition using OpenCV & Python 

HAR using OpenCV and Python is an interesting area I have been brushing up on lately. It comprises video stream or sequence analysis for detecting and categorizing human activities or behaviors. OpenCV, a strong computer vision library, gives a robust structure for processing video data. Techniques such as motion tracking, optical flow analysis and feature extraction, allow me to capture and interpret human movement in real-time. Python is an outstanding language for implementing the HAR algorithms as it is very simple and robust data handling.  

Through integration of machine learning models such as support vector machines or convolutional neural networks my models can identify activities with great precision. Such systems can be used in the areas of surveillance, sports analytics, healthcare monitoring and others, automating the identification of human actions. If you’re interested, here’s a helpful resource for implementing mage processing projects with source code in Python, Human activity recognition using open CV & python 

11.Image processing-based Tracking and Counting Vehicles 

Vehicle tracking and counting using image processing based technique has been an interesting project to me. Tasks like traffic management and surveillance require it. Via object detection and tracking algorithms from libraries like OpenCV in Python, I’ve been able to track vehicle movements in real-time from either live footage or video. This includes determining vehicles entering and leaving specified areas for the exact count. For those interested in delving deeper into the technical implementation, I recommend exploring the source code available in this GitHub repository, Image processing-based tracking and counting vehicles. Furthermore, if you are interested in other digital image processing projects using Python with source code, check out the other resources and source code available online. The projects are critical in traffic flow analysis, congestion management, and enforcement of traffic rules; information gained helps make rational decisions on traffic safety and efficiency of transportation systems in cities. 

12.Paddy crop disease detection using machine learning 

One of the interesting projects I got involved in was detection of the diseases in the paddy crops using machine learning. Agricultural productivity is critical to it. By using machine learning algorithms on image datasets comprising healthy and diseased paddy plants, I have been able to develop models which can accurately predict different types of crop diseases. These algorithms study particular features or signs characteristic of diseases, e.g., discoloration, lesions, or deformities, in plant images. These models can classify accurately the health of paddy crops utilizing methods like image classification or object detection. With the introduction of such systems farmers can rapidly identify and diagnose crop diseases thus timely intervention and controls to prevent severe crop losses. Such implementation of machine learning also improves agriculture productivity as well as promotes sustainable farming methods that minimize use of pesticides and facilitates better crop management techniques. 

For those interested in exploring the technical implementation, along with other image processing projects with source code in Python, I recommend checking out the following GitHub repository: Paddy crop disease detection using machine learning 

13.Smart Voting System through Facial Recognition 

Facial recognition based voting system development has been an interesting project for me. It strives to modernize and secure the voting process by incorporating state of the art technology. The system makes it simple, available and secure to cast one vote via camera captured images as identifiers. To guarantee the legitimacy of every vote we are using machine learning algorithms that match faces against the voter’s databases in order to prevent incorrect actions such as impersonation or double voting. Besides, this system facilitates inclusion for voters with disabilities, creating the possibility of independent participation. Implementing such a system promotes transparency, effectiveness and faith in the democratic system. 

For those interested in exploring the technical implementation, along with other image processing projects using Python with source code, I recommend checking out the following GitHub repository, Smart voting system through facial recognition 

14.Object Detection, convert object name to text and text to speech 

As part of my investigation into object detection, I probed an amazing zone where I convert detected objects into text, further translating them into speech. Using sophisticated computer vision methods the objects are localized in images or videos. Text-to- speech, consequently, is employed to convert these labels into spoken words that provide real-time auditory feedback. This technology is very promising in a lot of applications ranging from visually impaired individuals in navigating their surroundings to enhancing user experiences in augmented reality settings. For those keen on diving into the technical details, I recommend checking out the source code available in this GitHub repository, Object detection, convert object name to text and text to speech. Furthermore, there are lots of  digital image processing projects using Python with source code available online; you can check further resources and projects. 

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How Image Processing Helps In Image Processing Projects With Source Code?

Image processing as a concept allows the transformation and manipulation of multiple images at a given time. This also helps extract vital information from them to help with image processing projects with source code. Naturally, there are multiple applications associated with such image processing projects with source code. Python is a highly popular programming language used for the purpose of image processing. It has a host of libraries and relevant tools that help to achieve the tasks for image processing at a very efficient level. One of the most prominent use cases of image processing is found in medical image processing projects using Python. For instance, in medical image processing projects using Python, the detailed steps of image processing initiate a deep learning algorithm to extract useful insights from thousands of images and implement them in medical diagnoses. This helps obtain clearer images through noise reduction, leading to better-diagnosed images and accurate analysis for precise treatment. 

Python is a programming language but is significantly used for image processing purposes due to its ease and efficiency. It has amazing libraries as well as efficient techniques that process images finely, making it one of the most popular languages to be used for image processing projects. 


In this article, we have covered 14 image processing project ideas. These projects are not the end of your exploration. There are numerous applications of Image processing in every industry. The medical industry uses it for early cancer, malaria, and other diseases detection. This field requires a thorough understanding of matrix algebra, transformations, and various types of mathematical distributions. 

I hope you will learn a lot while working on these python projects. If you are curious about learning data science to be in the front of fast-paced technological advancements, check out upGrad & IIIT-B’s PG Diploma in Data Science and upskill yourself for the future.

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What is image processing and what are its application areas?

Image processing refers to the process of drawing out useful information from an input image or enhancing the input image to achieve the desired results. The real-time applications of image processing can be found in almost every domain:
1. The medical field uses image processing for analyzing test reports, x-rays, medical scans and UV imaging.
2. Computer vision primarily uses image processing and is used in various systems such as self-driving vehicles, 3D motion games, drones, and robotics.
3. Other applications of image processing include restoring old videos and images, pattern recognition, and multimedia security.

Name some of the most popular Python libraries for image processing.

Python is the most suitable language for image processing due to the feature-rich libraries that it provides. The following are some of the top Python libraries that make image processing very convenient.
1. Open CV
Open CV is hands down the most popular and widely used Python library for vision tasks such as image processing and object and face detection. It is extremely fast and efficient since it is originally written in C++.
2. Sci-Kit Image
The conversation over Python image processing libraries is incomplete without Sci-Kit Image. It is a simple and straightforward library that can be used for any computer vision task.
3. SciPy
SciPy is majorly used for mathematical computations but it is also capable of performing image processing. Face Detection, Convolution, and Image Segmentation are some of the features provided by SciPy.
4. Matplotlib
Matplotlib is a library generally used for data visualization in various forms such as scatterplots, bar graphs, pie charts, and line charts. It can also be used for image processing however, it does not support some file formats.

How can I make a smart traffic light system?

The smart traffic light is a common and interesting image processing project where the model analyzes the traffic situation and changes the lights accordingly. It captures the live images of the traffic. You can also feed the horn voices for even better performance.After analyzing the given data, it changes the colour of the light to green if the traffic density is low, yellow if it is medium, and red if the traffic is dense. For emergency vehicles like an ambulance, a bias could be added to the model too.

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