8 Best Image Processing Courses & Certifications in 2024
What is Image Processing?
Image processing is the process of manipulating or performing operations on images to achieve a specific effect (for example, creating a grayscale image) or obtaining some information from an image using a computer (for example, counting the number of circles inside it).
In simple words, it is the process of converting an image into digital form and performing certain operations to obtain some useful information from it. It is sometimes used in computer vision to enhance images at different scales, or as a data augmentation technique in deep learning.
Is Image Processing useful in Machine Learning?
Especially if you are working with data other than images, it isn't mandatory. Nevertheless, image processing and available tools can enhance machine learning. For example, you can improve detection results by denoising and enhancing images. So, it is not necessary, but if the domain is the right one, it can be helpful.
Top Image Processing Tutorials For Beginners List
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Best Online Courses to learn Image Processing for Beginners
Keeping this in mind, here at Coursesity, we have curated some of the Best Online Image Processing Courses with certification. Hope that you will find the best course for you to learn how to manipulate and edit an image to your desire with the help of certain algorithms and techniques depicted below.
1. Complete Guide to Image Processing with MATLAB
Understand the Theory of Image Processing, apply it in MATLAB, and design a GUI to interface it.
The course includes:
- Image Operations
- Image Histograms
- Image Filtering
- Image Thresholding
- Edge Detection in MATLAB
- Image Morphology
- Local Binary Patterns
This Image Processing course will forge a solid understanding of the basics of Image Processing in MATLAB. You will learn how to create a complete Graphical User Interface that includes most of the basic Image Processing Concepts.
Plus, you will understand most of the important concepts in a friendly manner.
You can take the Complete Guide to Image Processing with MATLAB certificate course on Udemy.
Course rating: 4.5 out of 5.0 ( 244 Ratings total)
Duration: 4 h
Certificate: Certificate on purchase
2. Fundamentals of Digital Image and Video Processing
Learn Fundamentals of Digital Image and Video Processing from Northwestern University.
The course includes:
- Introduction to Image and Video Processing
- Signals and Systems
- Fourier Transform and Sampling
- Motion Estimation
- Image Enhancement
- Lossless Compression
- Image & Video Compression
- Image & Video Segmentation
- Sparsity
This course will cover the fundamentals of image and video processing. It will provide a mathematical framework to describe and analyze images and videos as two- and three-dimensional signals in the spatial, Spatio-temporal, and frequency domains.
Also, you will not only learn the theory behind fundamental processing tasks including image/video enhancement, recovery, and compression - but you will also learn how to perform these key processing tasks in practice using state-of-the-art techniques and tools.
Plus, you will be introduced to a wide variety of tools such as – optimization toolboxes to statistical techniques. The course also gives emphasis on the special role sparsity plays in modern image and video processing.
You can take the Fundamentals of Digital Image and Video Processing certification course on Coursera.
Course rating: 4.6 out of 5.0 ( 1,736 Ratings total)
Duration: 36 h
Certificate: Certificate on purchase
3. Computer Vision and Image Processing Fundamentals
Learn about computer vision, one of the most exciting fields in machine learning. artificial intelligence and computer science.
Throughout this course, you will learn the basics of computer vision and its applications in many different fields. In this course, you'll work with Watson AI, OpenCV, and Python to process images. Additionally, you will learn how to build, train, and test your image classifiers.
In this Image Processing course, you will:
- Build, train, and test your own custom image classifiers.
- Various computer vision applications across many industries.
- Imaging processing and formation capabilities powered by AI.
- Utilize Python, Watson AI, and OpenCV to process images and interact with image classification models.
In the hands-on course, you will perform several labs and exercises. Upon completion, you will deploy your cloud-based computer vision web app. This course does not require any previous experience with Computer Vision or Machine Learning. However, some knowledge of Python would be helpful.
Course rating: 16,370 total enrollments
Duration: 3 weeks (3-4 hours/week)
Certificate: Certificate on purchase
4. Practical Image Processing in C/C ++ From Ground Up
Build an Image Processing Library in C/C++
The course includes:
- Setting Up
- Basic Image Processing Concepts and Terminologies
- Arithmetic Operations
- Histogram and Equalization
- Geometric Operations
- Gray Level Transformation
- Image Enhancement Techniques
- Edge Detection
- Neighborhood Processing
- Filter Algorithms
- Image Formation
With this Image Processing course, you will learn how to develop the 2-D Discrete Convolution and Edge-Detection Algorithms in C++. You will also learn how to create Spatial Filtering Algorithms in C++.
Plus, you will learn a series of extra things ranging from how to compute an Image Histogram and Equalize it in C++, to developing Gray Level Transformation Algorithms, suppress noise in images, and understand all about operators such as Laplacian, Sobel, Prewitt, and Robinson.
You can take Practical Image Processing in C/C ++ From Ground Up™ certificate course on Udemy.
Course rating: 4.6 out of 5.0 ( 1,529 Ratings total)
Duration: 36 h
Certificate: Certificate on purchase
5. Building Image Processing Applications Using scikit-image
Learn how to build Image Processing Applications from scratch using scikit-image.
The course includes:
- Working with Image Data
- Object and Feature Detection
- Segmentation and Transformation
- Applying Global and Local Thresholding Algorithms
- Image Segmentation and Region Adjacency Graphs
- Comparing Images Using MSE and SSIM
With this Image Processing course, you will gain an understanding of a few core image processing techniques and see how these techniques can be implemented using the scikit-image Python library.
First, you will learn the basics of working with image data represented in the form of multidimensional arrays. Next, you will discover how to manipulate images using the NumPy package, extract features using block view and pooling techniques, detect edges and lines and find contours in images.
By the end of this course, you will have a better understanding of a range of image processing techniques that you can use on your images, and you will be able to implement all of those using scikit-image.
You can take Building Image Processing Applications Using scikit-image certification course on Pluralsight.
Course rating: 4.5 out of 5.0 ( 23 Ratings total)
Duration: 1 h 48 m
Certificate: Certificate on purchase
6. Complete Python-Based Image Processing and Computer Vision
Learn Python Based Image Processing and Computer Vision step by step.
The course includes:
- Computer Vision with Python
- Python Image Analysis - Getting Started With Basic Image Processing in Python
- Introduction to Computer Vision
- Image Recognition - What is Machine Learning?
- Unsupervised Learning Methods
- Supervised Learning: Classifying Images
- Start With Deep Learning
- Deep Learning For Image Classification
- Transfer Learning
- Unsupervised Deep Learning
Initially, you will learn how to install and get started with the Python Data Science Environment i.e. Jupyter/iPython. You will learn how to Read In Image Data Into The Jupiter/iPython Environment.
The course will show you how to carry out basic Image Pre-processing & Computer Vision tasks With python. You will also learn how to implement Unsupervised Learning Algorithms (such as PCA) on Image Data.
Plus, you will learn how to implement Common machine learning Algorithms for Image Classification and Deep Learning Algorithms on Imagery Data. You will also learn how to get started with Tensorflow and Keras for Image processing with deep learning.
You can take the Complete Python Based Image Processing and Computer Vision certificate course on Udemy.
Course rating: 4.6 out of 5.0 ( 583 Ratings total)
Duration: 5 h 30 m
Certificate: Certificate on purchase
7. Robotic Vision: Image Processing
Learn how images are extracted and how to use this to create a robotic vision, from the Queensland University of Technology.
In this course, you will:
- Describe how images are represented in a computer.
- Describe the purposes of different types of image processing and feature extraction operations.
- Demonstrate basic coding in MATLAB for image processing relevant to robotics.
Initially, you will explore how computers process images and how images are represented in a computer to help you understand the fundamentals of robotic vision. You will learn how to identify the unique features of a shape and its perimeter to examine how robots can be programmed to see.
Next, you will delve into how images are processed, covering advanced techniques such as morphological image processing and gamma correction. You will be able to describe the purposes of different types of image processing to determine which is best for your operations.
By the end of this Image Processing course, you will have the practical skills and knowledge to apply advanced image processing techniques to robotics.
You can take the Robotic Vision: Image Processing certification course on Futurelearn.
Course rating: 4,276 total enrollments
Duration: 12 h
Certificate: Certificate on purchase
8. Android: Image Processing with Picasso
Learn Android Image Processing as a Beginner with Picasso.
The course includes:
- Getting Started with Picasso
- Retrieving and Displaying Images
- Controlling Image Transformations
- Working with Caching
- Managing Request Activity
In this Image Processing curse, you will learn how to manage and process images using Picasso. First, you will learn how Picasso is a popular, reusable, and lightweight library that reduces the technical problems of working with images.
Next, you will learn how to utilize Picasso’s powerful features, like how to load images from different source locations, and maintain performance with caching.
Finally, you will discover how to resize and transform images properly, manage request behavior, and much more. By the end of this course, you should feel comfortable building your own apps that display image content in dynamic ways.
You can take the Android: Image Processing with Picasso certification course on Pluralsight.
Course rating: 5.0 out of 5.0 ( 12 Ratings total)
Duration: 1 h 56 m
Certificate: Certificate on purchase
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