Abstract:
It is estimated that 285 million people globally are visually impaired, and
without additional interventions, these numbers are predicted to increase
significantly. One of the most difficult tasks faced by the visually impaired is
identification of people. The inability to recognize known individuals in the
absence of audio or haptic cues severely limits the visually impaired in their
social interactions and puts them at risk from a security perspective.
In this thesis Matlab software was used to simulate a system that aids the blind
person to recognize his family and friends facial images that are stored in a
database, and if a match is found on the database, the system will announce
the name of the person via speakers to the blind person. Two face recognition
algorithms will be used; Principle Component Analysis (PCA), and Hidden
Markov Model (HMM) to compare their performance. The simulation
considered the recognition of a static facial image (photo) and a live facial
image. The results showed that the PCA algorithm performs better than the
HMM. It has a small recognition time and work properly under different face
orientation.
