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Sustainability ReportOur sustainable development initiatives and annual reportGo Wombat builds computer vision software for established businesses that need visual inspection results connected to usable applications and traceability workflows. We develop the backend services, interfaces and integrations around the vision capability, with testing and ongoing support. Explore our electronics manufacturing experience in the Cybord case study.
Discuss your computer vision projectGo Wombat’s public Cybord case documents software delivery for electronics quality control and component traceability. Our listed responsibilities include backend and frontend development, project management, testing, and support. The case describes how inspection information becomes usable through dashboards and traceability views across production sites.
Our AI experts build custom computer vision solutions and provide support throughout all stages of your development project.
The analysis and segmentation algorithms define what a computer vision solution can do. Our developers have built applications that classify physical objects with accuracy that matches or exceeds that of people doing the same task.
Our in-house team includes technical project managers who can run your computer vision project and keep the developers working to the agreed plan.
Computer vision-as-a-service and off-the-shelf tools do not always fit the identification, tracking and labelling of objects in video and images. In those cases we build custom software that identifies and analyses still and moving objects and integrates with traffic systems and other networks.
Before development, our solutions architect and software engineers identify where computer vision can make your business more efficient and how best to build the solution.
Visual search lets users find products or content by uploading a photo instead of typing keywords. We build the image-matching back end and connect it to your catalogue.
We build video analysis software that extracts information from footage and detects events in space and time. Typical uses are intruder detection and automating manual monitoring tasks.
Computer vision is used in retail, medical imaging, construction, security and other industries to automate visual tasks such as inspection, counting and monitoring. Our consultants help you find where it fits in your business.
We also build computer vision features into mobile apps: visual search, object detection, tracking and labelling, and image segmentation and analysis.
We start with a call about your project. If we are a good fit, the project follows our standard software development process.
Computer vision has applications in almost any sector. These are the industries we work with:
What computer vision can do for your business:
Handle more work without growing your team.
Keep costs low while production volumes remain high.
Match or exceed the accuracy of manual checks with less effort.
Give users faster results at the same quality.
Grow your facility, platform, and business according to the demand.
Detect intruders and hazards in camera footage automatically.
Handle more work without growing your team.
Keep costs low while production volumes remain high.
Match or exceed the accuracy of manual checks with less effort.
Give users faster results at the same quality.
Grow your facility, platform, and business according to the demand.
Detect intruders and hazards in camera footage automatically.
We build these types of computer vision software:
Classify animals, vehicles, buildings, and much more within an image.
Identify and determine the location of objects in still images or video.
Monitor the movement of objects through recorded or live video.
Measure how objects move, including speed and direction, across a sequence of frames.
Reconstruct a 3D scene from a set of images or video frames.
Split an image into regions by assigning a label to every pixel, so each object or area can be analysed separately.
Analyse a video or image to identify a human or animal action.
Eliminate blur, noise, and other variables that distort an image.
Identify and label shapes, colours, and other pattern elements.
Computer vision pays off where people spend hours inspecting, counting or reading things in images and video, in a software product or an internal tool.
We have built several platforms that use computer vision.
Contact us to set up a call about your project.
Examples of our computer vision work.
Quality control automation system
Manufacturing, Artificial Intelligence/Machine Learning
February 2021 - Ongoing
Cybord removes counterfeit and defective components from production lines. Its technology uses AI and big data to identify counterfeit, defective and tampered components, including hardware-based cybersecurity threats. Defects are detected during component placement and before reflow, which makes rework simpler and products more reliable. Integration with manufacturing execution systems quarantines nonconforming materials so they cannot be used.
Object recognition software
Sports
2018-2019
The project is an object recognition system that identifies players during a cricket match. It uses specific movements and sound peaks as triggers to start recording the game stream automatically, so key moments are captured without manual intervention. By combining computer vision and audio detection, it supports game analysis, player tracking and performance evaluation for teams, broadcasters and analysts.
Computer vision is a field of computer science that enables computers to extract and interpret information from images and video. It uses AI and machine learning to automate tasks that would otherwise need human sight and judgement.
Computer vision systems identify, classify and analyse visual information faster and in larger volumes than people can. They locate and categorise objects and people in images and can trigger an action based on what they find.
For example, it can detect and recognise:
Plant diseases in agriculture.
Real vs. staged damage in auto insurance.
Faces for security applications.
Items for automatic checkout in retail stores.
Common types include:
Object recognition
Pattern recognition
Edge detection (i.e. identifying the boundaries of objects within an image)
Image classification
Object tracking (i.e. following the movement of objects in a video or in images)
Image segmentation (i.e. dividing an image into different regions based on visual characteristics)
Yes. Python is widely supported by computer vision libraries, and its readability makes it a popular language for computer vision work.
Computer vision and machine learning are related fields. Modern computer vision relies on machine learning, especially deep learning and convolutional neural networks, which are trained on images to recognise patterns in visual data.
