Backed by many years of experience building hardware and software for embedded systems, our team at Integra Sources helps businesses in the manufacturing, healthcare, and consumer electronics industries develop custom video and image analysis software for computer vision and machine vision systems. Our recent projects in this artificial intelligence field include a fall detection system for elderly care, a mobile app for detecting melanoma skin cancer, and an autonomous robotic lawnmower.
We provide R&D product development services for computer vision systems that extract, analyze and understand useful information from a single image or a sequence of images. We use computer vision libraries such as OpenCV, optimize existing methods, and create our own algorithms based on mathematical models. Within the scope of computer vision as a service, our goal is to build a system that has a high processing speed and doesn’t lose performance. For implementing computer vision projects, we also use artificial intelligence techniques such as deep learning and machine learning.
Being able to recognize whether an image contains a specific object is a primary task of a computer vision system. To detect objects we extract features from the region of interest (roi), then perform image classification and localization to know where in the image each object appears. We apply deep learning methods and computer vision techniques to develop object detection algorithms. These algorithms are applied to face analysis, handwritten character recognition, gesture recognition, machine vision, robots, and more.
Most of the time our video analysis algorithms are used in automated visual surveillance systems. These algorithms solve three tasks: 1) motion detection, 2) object tracking, and 3) scene understanding. To detect a moving object in the background of the scene we use background subtraction algorithms.
Object tracking relies on algorithms which have to find which object in a video frame relates to which object in the next frame. And the aim of scene analysis algorithms is to recognize activities in a scene. We apply rule-based approaches to identify abnormal behavior in the video frame and if it's detected, our system triggers a specific action like an alert or a call to the ambulance.