Colors are powerful tools that influence our thoughts, feelings, and actions, and knowing how they work can help us in many different areas of life. Colors can alter brain activity, emotional states, and cognitive functions and affect how we perceive the world visually. These effects are measurable in electroencephalogram (EEG) signals, reflecting different brain activity states in response to color stimuli. Understanding these impacts can be valuable in design, marketing, therapy, and neuroscience. The chromatic response on EEG signal generated for static color visualization is commonly known as visual evoked potential (VEP), and this VEP can be used to generate control commands for brain-computer interface (BCI) applications. This study explores the possibility of using EEG signals induced by primary color visualization to provide control mechanisms for BCI applications. By analyzing EEG signal patterns generated during the visualization of primary colors, this research aims to discriminate these patterns effectively. The study also investigates how black and gray background colors affect the perception of primary colors. The findings demonstrate that EEG signals related to RGB color stimuli can be distinguished with a mean accuracy of 97.08% using minimal selected features and channels, improving existing methods. This research highlights the potential for using color-induced EEG signals in BCI applications, providing a new avenue for control modalities.