Detection and Tracking Shape-Shifting Gold Necklaces Using Computer Vision Techniques

Due to the current method of theft in gold shops, criminals were stealing gold necklaces or gold jewelry. They were concealing it, which employees did not know that gold had disappeared from the gold shop. The shopkeeper found it difficult to track directly from the object and physical gold necklaces were small for easy stacking. This research focuses on a study and analysis of the detection and tracking of deformable gold necklaces. Therefore, it was observed in many follow-up experiments. After that, the researcher presented the detection and tracking of deformable gold necklaces had been using image processing techniques. The researcher will improve the gold necklace tracking performance with the traditional Gaussian mixture model (GMM) enhanced with the adaptive background subtraction (ABS) functionality. We compared the traditional GMM method and the optimized GMM with an adaptive background subtraction (ABS) image. The results of the experiment were shown in the method to compare efficiency before and after improving efficiency. It was found that 86.07% of the frames could be tracked properly.