A sliding window is very important tool in image processing and computer vision algorithms. Here is my code for a generic sliding window implementation. It is a very fast draft so may contain bugs. Use it at your own risk. You must acknowledge my name (Md. Iftekhar Tanveer) and email address (firstname.lastname@example.org) if you use it in your code.
The featured image shows the primary use case for my software FEPS. Check the contributions page for corresponding paper and other information.
Here is another way to use the feature detectors. Instead of using the general FeatureDetector interface, here each feature-detector class is called individually and the associated functions are called.
Feature detectors and describers are interesting topics in computer vision. People have found that detecting edges and corners in an image is useful for many different application, for instance, image matching, stitching, tracking etc. I was playing with the OpenCV image detectors today. This post is the outcome. Here I give the code and the performance of several feature detectors in my machine.
From October 22nd to October 24th, we (Me and Iftekhar Anam) attended the ASSETS 2012 conference in Boulder, CO to demonstrate our sensory substation system named “FEPS”. It was an amazing experience to meet all the major researchers on accessibility and assistive technologies for disabled people. In this writing, I am going to share my experience of attending this conference.
For ease of thinking, take the study of differential equations, recurrence relations etc. 1. Knowledge on the rule – if this, do this then you’ll get the solution 2. Knowledge on the proof – Is it really true that in ALL cases if I follow the rules, I’ll get the solution? 3. Knowledge on the design – How should I design the rules for more complecated cases? 3 or 4. Knowledge on the Big Picture – how the different elements interact? Why the designs are being so?
In the last post, we saw the basic methods to load and display matrices. Let us see some more aspects of an OpenCV matrix. Matrix Assignment and Cloning In opencv, the assignment (“=”) operator does not copy a matrix. It only attaches a new label or alias to a matrix. In c/c++ when we write A = B, we expect A and B to be two different variables with same value. However, in OpenCV, such an assignment operation will actually say that A and B are invariably the same matrix. This will be illustrated in the following opencv snippet.
I know many people will look at me in frowning eyes after reading the title. Yes, OpenCV is an image processing and computer vision library. But believe me, the most rudimentary works you need to do in these fields are essentially “Linear Algebra”. Think about an image — it is a matrix; and most of the time you’ll work on matrices. Even other data structures like vectors and points — all are some kind of matrices. Necessity of doing linear algebra is one of the main reasons for burgeoning MATLAB (which is an acronym for MATrix LABoratory) libraries for image processing. In fact, …
Last night was a night of biggest moon for this year. I tried to capture some pictures of the moon using my Canon EOS Rebel T3. It was getting overexposed in the beginning. The picture was looking like a bowl of white milk. Then I started reducing the exposure by increasing the shutter speed while keeping the ISO fixed to 100. Then I got a shot. How is it?
The new OpenCV C++ interface has made the process of image loading and display much easier. If you are a bit familiar with MATLAB then it is even more easier for you. Because in many cases, the MATLAB function names are directly used in OpenCV.