Object detection and classification by cascade object training

Computer Vision (CV) has become ubiquitous in smart systems for detecting and labeling objects, starting from social media platforms to autonomous vehicles. It requires extensive computation and image processing. In this paper, a model is processed and used to detect various colored cups with saucers from a set of different objects. The system is trained using Cascade Trainer Graphical User Interface (GUI), and the testing is done utilizing MATLAB, discussed in detail. Finally, the model is tested for its efficacy on the S32V234 Evaluation Board (EVB). Our proposed system accomplished its goal by identifying and tagging the objects of interest with maximum possible accuracy.