Some weeks ago I received an e-mail from a reader pointing to an interesting task in the field of image processing. He kindly let me to publish the problem and the images we were working on, so I decided to explain the problem and write a small guide showing how such a task can be solved.
Some weeks ago someone posted me a problem on segmenting regions of an image by using color information. She also attached a sample source code for doing this task. In this post this source code is analyzed and we also create a much better and general solution.
Although there are some great built-in functions in MATLAB to find local maximas, in this post a simple, convolution-based approach is demonstrated to practice using this operation. This post may inspire some MATLAB users to creative ways of using convolution in daily programming tasks.
This application is based on the previous post: A tutorial on intensity transforms of images. It requires only a modern web-browser to run.
Image processing often requires transforming the intensity values for example to turn the image easier to process or to highlight certain objects. In this post an effective way of some simple transforms are explained and an interactive demonstration is also available.
The rand function in MATLAB returns uniformly distributed pseudorandom values, but we often need random numbers of other kind of distributions.
A great article written by John S. Denker explains a method of generating random numbers with arbitrary distribution. This post is based on his work, and shows a simple MATLAB implementation.