This paper presents a comparative analysis of two methods for Region of Interest (ROI) detection and tracking: the well-known Feature Extraction Method (FEM) and the newly proposed Brightness Differences Matrix Comparison (BDMC) Method. Both methods were evaluated across various experimental conditions, including video quality and object characteristics, to assess their performance in terms of accuracy and processing speed. Results show that BDMC is approximately 20 times faster than FEM, due to its simpler computational structure, making it effective in real-time applications where rapid object tracking is essential. FEM, although slower, demonstrated robustness in recognizing and tracking objects with significant perspective changes and inconsistencies, highlighting its utility for tasks that require high object detection accuracy. The findings suggest that BDMC is more suitable for applications with low computational resources.