9 – Haar Cascades

Let’s build on top of our knowledge about feature extraction and object recognition, and think about how we might be able to simplify and speed up this whole pipeline. In this example, we’ll be building a face detector working with an algorithm called Haar cascades. This algorithm works by training on many positive images (images … Read more

8 – Hough Line Detection

In this notebook, I’ve read in and made a copy of an image of a hand holding a mobile phone. Now, let’s say we want to isolate this screen area. By using the Hough transform, we should be able to detect the lines that form the screen boundary. To perform Hough line detection, I’ll first … Read more

7 – Hough Transform

The simplest boundary you can detect is a line, and more complex boundaries are often made up of several lines. For example, in document or photo scanning, documents are typically rectangular, and so their boundary can be thought of as four lines placed together. And when you do edge detection, you’ll find that edges when … Read more

6 – Canny Edge Detection

Now, we’ve seen the importance of using both low pass and high pass filters for accurate edge detection. But even with these used together, edge detection is still a very complex problem. We have to think about what level of intensity change constitutes an edge, and how we can consistently detect and represent both thin … Read more

5 – Gaussian Blur

Instead of using an all around averaging filter, we may want to filter that both blurs and image and better preserves the edges in it. And for that we use gaussian blur. This is perhaps the most frequently used low-pass filter in computer vision applications. It’s essentially a weighted average that gives the most weight … Read more

4 – Low-pass Filters

Earlier you saw an example of noise in an image of San Francisco City Hall. This noise is generally seen as speckles or discoloration in an image and it doesn’t contain any useful information. It might even mess with processing steps such as an edge detection when high pass filters can amplify noise if it’s … Read more

3 – Creating a Filter

So let’s see how to create our own high pass filter. First I’ll show you how to define your own custom kernel and later we’ll use openCV functions to help us build commonly used filters. Here’s an image of a building. It’s actually San Francisco City Hall. I read it in and as usual I’ve … Read more

2 – High-pass Filters

In image processing, filters are used to filter out unwanted or irrelevant information in an image or to amplify features like object boundaries or other distinguishing traits. High-pass filters are used to make an image appear sharper and enhance high-frequency parts of an image, which are areas where the levels of intensity in neighboring pixels … Read more

1 – Nd113 C7 36 L Filters And Finding Edges V1

Now, we’ve seen how to use color to help isolate a desired portion of an image and even help classify an image. In addition to taking advantage of color information, we also have knowledge about patterns of grayscale intensity in an image. Intensity is a measure of light and dark similar to brightness, and we … Read more