Computer Vision and Image Processing with Open CV

Learning from passion projects to move towards facial recognition and emotional detection, I’ve learned that Objective-C is a strict superset of C, and you can mix it with C. OpenCV which is a computer vision framework is written in C++. In order to use it within an iOS project, we have to use Objective-C++, which is a combination of C++ and Objective-C syntax. This allows me to reuse your C++ code such as the OpenCV library. Nonetheless, Objective-C is the main language for iOS in which I received a crash course in life three time using the language in order to get paid and grow as a developer.

Today, I’ve challenged myself in introducing myself to the OpenCV framework in which I always saw it as something monumental. Like anything in life, you will fall down a couple of times but you have to focus on your human will to overcome such challenges. I did have a troubling experience adding an OpenCV module which doesn’t come with the standard download that’s maintained more often in open source. I kept receiving a binary linking problem with the module I was in desire of. Xcode had an issue with not seeing the header file to reference a function call in the third party library. Getting started with OpenCV was definitely a crash course in linking third party frameworks.

OpenCV also taught me a new perspective in regards to the abilities of cameras on iDevices. I’ve gained higher knowledge in regards to the camera’s diagonal field of view, the focal length for zoomed in with the blurry affect in photos, the importance of carbon fiber tripods to reduce motion blurs, and lens attachments similar to higher definition cameras. For the image processing project, I was able to take an MRI image and apply color changes to the photo which was an introduction to how computer vision perceives and manipulates photos for artificial intelligence. See the video of the iOS application below: