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Software Development Services for Computer Vision

Object detection. Video analysis.
What we do
What’s included

What we do

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.


What's included?

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. 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.

Object detection

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.

Video analysis

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.


Check out our recent case study

Machine learning R&D Startup Smart home Healthcare Computer vision

Algodroid R&D Project: Building a Computer Vision System for Preventing Falls in the Elderly

The project is a video monitoring system that uses computer vision and machine learning to track people's activities throughout the day and detect falls in real time.

Our clients include enterprise companies, research centers, and innovative startups from all over the world

How we work

Check out the table below to learn more about how we work and where your involvement is most needed depending on the type of collaboration model.

AREA OF RESPONSIBILITY

PROJECT-BASED OUTSOURCING

DEDICATED DEVELOPMENT TEAM

RESEARCH & DEVELOPMENT

PROJECT REQUIREMENTS

YOU

SHARED

YOU

UI DESIGN

SHARED

SHARED

SHARED

ENGINEERING

INTEGRA

INTEGRA

INTEGRA

DEVELOPMENT

INTEGRA

INTEGRA

INTEGRA

TESTING

INTEGRA

SHARED

SHARED

DELIVERY MANAGEMENT

SHARED

SHARED

Frequently Asked Questions

Read this information to better understand the process of software development for computer vision.

What is computer vision?

Computer vision is a part of artificial intelligence that aims to give computers the capability to understand a single image or a sequence of images. This is achieved by developing computer vision algorithms that simulate a human visual system and make decisions based on what they see.

What is machine vision?

Machine vision typically refers to using computer vision in industrial automation and robotics.

What technologies do you use to develop computer vision systems?

We use the following programming languages and technologies:

Languages: C++, Python

Frameworks: OpenCV, TensorFlow, Caffe, Caffe2, FFmpeg, DirectShow, OpenALPR, Tesseract.

What computer vision applications have you worked with?

We have extensive experience in computer vision software development. The core applications we've worked with include image understanding and video analysis (after all, videos are nothing but a collection of images (frames)). Here are the common tasks we've solved:

  • Image segmentation
  • Object detection
  • Object recognition
  • Object tracking
  • Feature extraction
  • Feature and color correction
  • Face detection
  • Image stitching

What methods do you use for object detection?

To detect objects in an image we use color extraction, shape extraction, background removal algorithms, and machine learning methods.

What methods do you use for video analysis?

For video analysis, we use motion detection, human detection, and object tracking methods.

How does R&D product development work?

If you aren't sure whether your project is feasible, we can help you figure it out. Our R&D model is made for complex projects with a high degree of uncertainty. Here is how it works: we'll study your requirements and propose some hypothesis on how the problem can be solved, and how much it might cost. During project development, we'll run several experiments to find the most viable implementation and build the solution for you. If we find out that your project isn't feasible, we will let you know t early on.

To build a computer vision system I need lots of data. Where do I get them?

Of course, it's best if you could provide us with the datasets. If it's not possible, we'll dig for images in open source databases.

Where have you applied computer vision algorithms?

Some examples of our projects with computer vision include a video monitoring system for fall detection for elderly care, a SkinView app for detecting melanoma skin cancer, and a video surveillance system for tracking football players on the field.