In the last few years we could notice that camera’s quality has been improved, its price has decreased at a point where we can find them almost everywhere. Most smart phones, if not all, have one or even two cameras. Youtube, Netflix, Flickr, Instagram are among the most popular websites around the world. At the same time, microprocessors became more powerful and cheaper in the way that programs can process image and video in real time.
Continue reading Camera Calibration – Part I
Hello,
In the last post I explained briefly what are histograms and today I’ll continue a little more and show how it can be useful to process images. Some examples of how histograms can be used are: image enhancement, texture classification, image segmentation, etc. In this post I’ll cover the most common use for histogram which is histogram equalization. Continue reading Histogram equalization
Hello there,
Today I’ll cover a simple subject, image histogram. What is a histogram? Histogram is a graphical representation of a set of data separated in differents classes. It is represented by vertical bars where the base represents the class and the height represents the frequency/quantity of how many times it happened. Yes, it seems to be more complicated when we try to explain something really easy. Look at the figure 1 below Continue reading Image Histogram
Hi,
Today is a small how to install OpenCV + QT5 in linux Ubuntu. For those who doesn’t know what is OpenCV, you can check here. Briefly OpenCV is a library for real time image processing created by Intel. It’s free for use under BSD license. Continue reading Installing OpenCV 2.4.9 + QT5 in Ubuntu
Hello there!
More than 6 months from last post, for a good reason. We had our third kid and now, time is more than ever a scarce resource. So, let’s stop talking and go direct to the point!
Today I’ll explain a little about Baye’s theorem and why it’s important to know it. Baye’s theorem is named after, Thomas Bayes an English statistician. This theorem is a solution to solve a problem of inverse conditional probability. I’ll give you an example to have a better understanding:
Hello there! In this post, as promised, I’ll explain a little about vector quantization. I’ll try to explain more how it works and not focus in the math, ok?
So, what’s the main idea behind vector quantization? The idea is pretty simple. Continue reading Vector quantization
Hello there!
Some posts ago I wrote about digikey’s continuing education program, if you didn’t read it, there is the link.
In the next five days, they are discussing about embedded vision, so if you are interested, check it out here. Continue reading Digikey – 180 days of education – Embedded Vision
Hello!
Today I’ll explain a little about scalar quantization. The goal of scalar quantization is to try to display an image using less quantization levels or less bit to represent each color level.
This method is very simple and very intuitive but the results aren’t that good. So, what’s the idea of scalar quantization? Imagine that we have an RGB image with color quantization from 0 to 255 (8 bits) and we want to represent the colors level only with 2 bits for each color. So instead of using 24 bits we’ll use only 6. Continue reading Scalar Quantization
Hello there!
This post is about ordered dithering in Octave. What’s is dithering? You can find a very good explanation here in wikipedia. But briefly, the idea of dithering is to create the illusion of color depth in images with (in our case) only two color quantization. This technique is used in printers, scanners, etc. We print small dots black and leave white spaces and our eyes will do the rest of the job. For those who doesn’t know, our eyes has a low pass filter as frequency response.
Hello there!
Here a simple “how to” to install packages on Octave.
I'm an electronics engineer with 10+ years of experience in embedded system, hardware and firmware development for several 8/16/32 bits microcontrollers like 8051, Microchip, MSP430, Freescale, ARM, etc. I'm a passionate in electronics and embedded systems, but not a nerds! =P
