Recognize objects. Identify differences. Spot similarities.
We can build Image Recognition Software customized just for you.
Find, classify, count and measure objects and activity with custom recognition software.
Spot similarities and differences.
Custom software quickly identifies unique characteristics among similar items. For example, one pattern with multiple sizes and colors.
Quantify traits and patterns in images.
Count and measure attributes like skin tone, hair and wrinkles.
Find unknown part numbers.
Recognize parts by comparing on-site photos with images in a database.
Pinpoint and compare changes.
Analyze the differences in sequential images.
Scrutinize a group of photos or videos for an object or scene.
Computer vision lets you isolate images with the content you seek.
Spot gestures in photos or video.
Custom recognition software pinpoints motions, gestures and facial expressions.
Recognize unique objects by distinctive features.
Use an area-of-interest to mark the traits that uniquely identify an object, just as a fingerprint identifies a person.
Sort and count similar items.
Identify, classify, and count objects based on their many traits and distinctions.
Extract information from images and videos
Put Computer Vision and Image Recognition to work for you.
- Recognize single patterns from many possibilities
- Recognize a SKU from a photo using preexisting image banks
- Identify make and model of an item using photo pattern recognition
- Automatically identify features of an image and take measurements
- Recognize and monitor items in videos for measurements and tallies
- Identify and track objects in motion in videos
Custom, easy-to-use, computer vision software development.
Your image recognition software is custom-made to meet the demands of your specific use case.
The software we develop takes advantage of Computer Vision using video and image processing in combination with machine learning techniques to satisfy a variety of needs including object recognition, tracking, counting, and measuring.
Our software engineering team focuses on creating easy-to-use applications that dramatically accelerate productivity.
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Which Image Recognition Strategy Best Suits your Use-case?
Using Traditional Algorithms
Traditional algorithms are appropriate when the item can be recognized using known patterns and rules. For example, identifying a part in inventory based on its shape, colors and surface qualities. Or identifying an assembly from its components.
Using Machine Learning Algorithms
Machine Learning algorithms are appropriate when the items of interest share common characteristics and a large number of factors affect the identification. In order to develop recognition software with Machine Learning, many sample images are required.
Combine both Sets of Algorithms
Many times, both sets of algorithms are needed to get results.
Find out how feasible your project is and what it might cost
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