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Introduction “In computer vision and image processing the concept of feature detection refers to methods that aim at computing abstractions of image information and making local decisions at every image point whether there is an image feature of a given type at that point or not. The resulting features will be subsets of the image domain, often in the form of isolated points, continuous curves or
Cloud image processing using OpenCV and Node.js August 19, 2013 by Ievgen Khvedchenia A long time ago i was playing with cloud-based image processing. The first reason why i didn’t shared a reciple how to compile OpenCV as native app for windows azure cloud was trycky build process. It was too complicated and this tutorial will become outdated very quickly. The second one – Azure hosting wants a l
OpenCV library is widely used by computer vision engineers across the world. It contains almost all algorithms you may want for R&D or product development. It has production-ready build farm with tests and strong community that give nice feedbacks and discover errors. But nevertheless OpenCV has some strange issues and undocummented behaviour that can surprise you as minimum and crash your app as
I think developers and research guys who works with object recognition, image registration and other areas that uses keypoint extraction can find this post useful. Recently (from 2.4.2) a new feature descriptor algorithm was added to OpenCV library. FREAK descriptor is claimed to be superior to ORB and SURF descriptors, yet it's very fast (comparable to ORB). Also people in comments on my blog men
After publishing Building OpenCV for iOS article many of readers asked me how to use OpenCV within ObjectiveC code, because they encountered compilation errors. In this post I'll show you how to use OpenCV and ObjectiveC to make some image processing. In this post I'll use GLImageProcessing sample demo from Apple. Also you will need precompiled OpenCV for iPhone. How to make it read here. I've cop
Introduction Here is an update of half year-old post about differences between existing feature detection algorithms. Original article can be found here: Comparison of the OpenCV's feature detection algorithms – I. I decided to update this comparison report since many things happened: OpenCV 2.3.1 has been released and the new type of feature detector (ORB feature detector) has been introduced. OR
Almost all image processing algorithms uses gray scale images as input source. But almost all hardware video sources provide frames in RGB/BGR(A) formats. So gray scale conversion is very popular operation. Although it's expensive enough to cause CPU-bound bottlenecks while running on mobile processors. In this post i will show you how to use ARM NEON intrinsic to get significant performance boost
A story about me competing against top-performing individuals and teams from domain-expert businesses, crunching 2.5Tb of dataset, figuring out how to deal with label noise, changing competition metric, and finally, winning. Introduction I usually start each new solution by creating a solid baseline from scratch, without looking to provided baselines. To my beliefs, it helps to build a deep unders
My first post in this blog was about building OpenCV for iOS devices (iPhone, iPad, iPod and so on). But the build process that i used is not trivial at all. I received a lot of feedbacks and questions about building OpenCV, setting up XCode build environment. Today i made your life much easier. I have a gift - a build script, which will build OpenCV library for your iPhone, iPad, iPod or any othe
OpenCV (Open Source Computer Vision) is a library of programming functions for real time computer vision. This library has a huge number of algorithms.OpenCV supports Windows and Linux platforms (and Android starting from 2.2 version). But, unfortunately, there is no official iOS platform support for this moment. In this post i will show you that can build OpenCV for this platform and run it on yo
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