Building Image Processing Applications Using scikit-image

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Janani Ravi

1:49:16

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1. Course Overview

1. Course Overview.mp4

01:59

2. Working with Image Data

01. Version Check.mp4

00:16

02. Module Overview.mp4

01:02

03. Prerequisites and Course Outline.mp4

02:01

04. Introducing scikit-image.mp4

04:37

05. Working with Images as NumPy Arrays.mp4

05:54

06. Masking Images Using Array Manipulation.mp4

03:41

07. Masking Color Images.mp4

03:46

08. Introducing Block Views and Pooling.mp4

03:03

09. Block Views and Pooling Operations.mp4

03:58

10. Contours.mp4

05:35

11. Convex Hull.mp4

03:09

12. Edge Detection.mp4

03:32

13. Roberts and Sobel Edge Detection.mp4

01:20

14. Canny Edge Detection.mp4

05:47

3. Object and Feature Detection

1. Module Overview.mp4

01:13

2. Feature Detection and Image Descriptors.mp4

02:47

3. Visualizing Daisy Descriptors on Images.mp4

03:08

4. Visualizing Hog Feature Descriptors.mp4

03:13

5. Corner Detection.mp4

04:51

6. Introducing Denoising Filters.mp4

01:58

7. Applying Denoising Filters.mp4

05:02

8. Morphological Reconstruction.mp4

01:51

9. Filling Holes and Finding Peaks Using Erosion and Dilation.mp4

05:01

4. Segmentation and Transformation

01. Module Overview.mp4

01:02

02. Introducing Thresholding.mp4

02:06

03. Applying Global and Local Thresholding Algorithms.mp4

03:32

04. Image Segmentation and Region Adjacency Graphs.mp4

02:01

05. Segmentation and Merging Segments Using Rags.mp4

04:42

06. Introducing Watershed Algorithms for Segmentation.mp4

01:38

07. Segmentation Using Classic and Compact Watershed.mp4

03:00

08. Applying Image Transformations.mp4

02:37

09. Introducing the MSE and SSIM as Distance Measures.mp4

02:34

10. Comparing Images Using MSE and SSIM.mp4

05:37

11. Summary and Further Study.mp4

01:43

Description

In this course, you'll explore the scikit-image Python library which allows you to apply sophisticated image processing techniques to images and to quickly extract important insights or pre-process images for input to machine learning models.

What You'll Learn?

In this course, Building Image Processing Applications using scikit-image, you’ll 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’ll learn the basics of working with image data represented in the form of multidimensional arrays. Next, you’ll discover to manipulate images using the NumPy package, extract features using block view and pooling techniques, detect edges and lines and find contours in images.

Then, you’ll explore various object and feature detection techniques using the DAISY and HOG algorithms to extract image features, along with using morphological reconstruction to fill holes and find peaks in your images.

Finally, you'll delve into image processing techniques that allow you to segment similar regions in your images and apply complex transformations by exploring the Regional Adjacency Graph data structure to represent image segments.

By the end of this course, you’ll have a better understanding of a range of image processing techniques that you can use on your images, and you’ll be able to implement all of those using scikit-image.

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Python

Janani Ravi

Instructor's Courses

Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework. After spending years working in tech in the Bay Area, New York, and Singapore at companies such as Microsoft, Google, and Flipkart, Janani finally decided to combine her love for technology with her passion for teaching. She is now the co-founder of Loonycorn, a content studio focused on providing high-quality content for technical skill development. Loonycorn is working on developing an engine (patent filed) to automate animations for presentations and educational content.

Pluralsight

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Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.