There are a number of fundamental basic filters that are key to general image processing. After learning about the concept of a filter template and its use, learn how to utilize the blur, dilation, and erosion filters in OpenCV. These filters have many use cases, often as preprocessors to additional, more advanced image processing or manipulation.
- [Instructor] In this module, we will take a look…at a few useful filtering functions…often used to pre-process or adjust an image…prior to doing more complex operations.…These operations help reduce noise…or unwanted variances of an image or threshold.…The goal is to make the image easier to work with.…The three filters are the Gaussian Blur,…Erosion, and Dilation filters.…The Gaussian Blur filter smooths an image…by averaging pixel values with its neighbors.…It's called a Gaussian Blur because…the average has a Gaussian falloff effect.…
In other words, pixels that are closer to the target pixel…have a higher impact with the average…than pixels that are far away.…This is how the smoothing works.…It is often used as a decent way…to smooth out noise in an image…as a precursor to other processing.…Let's see how to use Gaussian Blur as an open CV.…Now opening the script editor,…I have the Chapter 2, Module 6 file open,…noting that we have already loaded in an image.…Let's first start off by showing the original image…
AuthorPatrick W. Crawford
- Installing and configuring OpenCV
- Data types and structures
- Image types
- Manipulating pixels
- Scaling and rotating images
- Using video inputs
- Creating custom interfaces
- Object detection
- Face and feature detection
- Template matching
Skill Level Intermediate
NumPy Data Science Essential Trainingwith Charles Kelly3h 54m Intermediate
Python: Programming Efficientlywith Michele Vallisneri2h 15m Intermediate
1. Install and Configure OpenCV
2. Basic Image Operations
3. Object Detection
4. Face and Feature Detection
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