Image Segmentation Innovations

Here, we segment an image into multiple homogenous regions based on particular patterns of similarity. With this technique, each region can be analyzed individually and contrasted with other regions. This categorization helps to better tag people, label objects, recognize faces, control traffic, and many other tasks. 

Humans can distinguish an object or person from the surrounding environment by demarcating boundaries and performing a comparative check with memories or other records of similar items. However, for computers to classify things, they need a specific context to classify things in pixelated regions. We train our computer vision models to distinguish signals from noise to perform efficient pattern recognition.

The first stage of intelligent image analysis is object detection. Our software uses many distinguishable properties that each object possesses to classify objects. We combine this operation with a database of existing images allowing the software to “learn” and better classify the objects. With our computer vision models, our software can provide accurate detection results and facilitate processes like property maintenance and store inventory management, among others. 

We can train our computer vision apps and models to identify objects and even faces. Once a face is identified, the computer vision model can compare it with an existing database of faces and identify the face if the record is present in the database. This technology has wide application, including in industries such as traffic management, healthcare, policing, security, HR, and more.