While this course only covers a few basic ways to identify and characterize image objects, there are many other applications and advanced techniques, as well as applications for objects identified in an image or sequence. Patrick briefly covers some of the other capabilities with OpenCV for more advanced applications, such as optical flow and object tracking.
- [Male Instructor] In this chapter,…we reviewed a few ways to approach…segmenting out objects in an image…and detecting properties of those objects.…A few areas we looked at included both…simple and adaptive thresholding using edges…to help break down apart closely fitting objects.…We also briefly looked at how to composite…multiple thresholds of different types together,…and in the last chapter, we saw how to use…Gaussian blurs to reduce noise,…and dilation and erosion filters to…reduce small speckles or gaps.…These are just some of the image processing tools…helpful in segmenting out objects.…
It's important to keep in mind the context.…Know what the application will be used for,…and develop segmentation that will fit the use case.…Do you know that your lighting will always stay…roughly the same for different image inputs?…If so, it may be more effective to use…non-adaptive thresholding; perhaps you can…improve your thresholding by gathering…your own global average or mean.…How about object orientation and scale?…
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
Python: Programming Efficientlywith Michele Vallisneri2h 15m Intermediate
NumPy Data Science Essential Trainingwith Charles Kelly3h 54m Intermediate
1. Install and Configure OpenCV
2. Basic Image Operations
3. Object Detection
4. Face and Feature Detection
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