Futuristic study of a criminal facial recognition system using open-source images

Face recognition provides an uncertainty challenge to criminal face identification. Thus, this recognition has many uses, from security to entertainment. Even if other bio-metric characteristics like iris and fingerprints are reliable, a person must be present to use them. Therefore, they are not the best tool for thieves to use for authentication. Anyone can recognize a criminal in an image by using face recognition technology in conjunction with a criminal database that contains the individual's personal information. In addition to needing great accuracy, a criminal recognition system also needs to be flexible to numerous variations in illumination, occlusion, maturity level, postures, etc. We use the Haar cascade and Histograms of oriented gradients (HOG) recognition learning systems discussed and contrasted in this study. We assessed models and HOG outperformed the criminal recognition system. We also go through several practical uses for this criminal recognition.