Our Smart-AI driven IFF target recognition function is to interpret the scene and/or to distinguish different objects from an image.  The goal of tracking is to detect moving objects and to pursue the objectives of interest by estimating their direction of movement, speed, and possible destination. In addition, automatic target recognition is a technique to identify objects or targets by comparing images acquired in real time with data stored in the database.  This is particularly useful in disposable applications which can enhance missile and UAV guidance capabilities.

Target recognition and tracking missions, image matching are crucial steps to compensate for background motion.  Subsequently, we introduce typical target recognition and tracking methods, and the application of image matching therein.

On the basis of the assumption that visible images of the target are available as a priority, our algorithm is able to recognize objects between IR and EO images under various conditions.  Edge detection and binary template matching were exploited to initialize IR and EO images, followed by a local fuzzy threshold to recognize highly similar objects stored in our database.

Our system employs an ensemble of state-of-the-art technologies for automatic airborne asset recognition and tracking in forward-looking IR and EO images in backgrounds by means of employing image segmentation and merging techniques to detect reliable targets from complex environments and environmental conditions, followed by training Bayesian-like convolutional classifiers to complete the classification and persisting results for post-mission improvements in detection and tracking performance.

Our system utilizes a unique framework specialized for machine intelligence corresponding to moving object detection, in which feature point selection and registration accuracy prediction are utilized to boost detection accuracy.

Our system addressed the challenges of mixing camera motion and object movement in moving object detection and tracking.  By using a Kalman filter based on the center of gravity of a moving object region in the minimum bounding box for tracking and identifying multiple moving objects.

Our Smart-AI IFF system is a must have add-on to any Missile or UAV with a one-way mission.  Future proofing an investment is also a must have as emerging technologies in AGI, Cognitive and Neuromorphic Computing are part of the R&D roadmap.