Forensic Art with Image Recognition and Brain Computing Interface

Abstract

This project uses software to generate forensic facial art by obtaining information directly from the human brain via a BCI headband. We can quickly cut the time necessary to design the victim's face by automatically picking the pre drawn structure. The above suggested approach will not only sketch the victim's face, but it will also search the criminal database at random to see if the victim's face has previously been recorded. First, we use the Brain Computing Interface Band to get the EEG signal from the witness's brain. The EEG data is then processed in bit Brain to categorise it into each instruction, and the classified signal is then moved to the next phase to choose the face portion. This study includes the previously collected pre-drawn facial components and categorized the images by this point. The CNN algorithm is significantly more accurate in classifying the images, and the classified images are saved with the trail in BCI computing to select the image in an accurate way. A categorized image data collection is used to generate the processed EEG signal. to discover the face region that is equivalent to an EEG signal. Drawing software was used to choose the selected face portion, which was then placed at the fundamental facial structure. When the painting is 40% complete, the face structure is compared to an existing criminal database to check whether the facial structure matches any previous crimes. This initiative aids in the identification of criminals and the creation of forensic art in considerably less time than the traditional method.