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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.
Image Processing Projects Using Python
Here we present you a list of 7 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.
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.
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.
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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!
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.
In this article, we have covered 8 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.
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.
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.
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.