  Over the years, advancements in the fields of digital image processing and
artificial intelligence have been applied in solving many real-life problems.
This could be seen in facial image recognition for security systems, identity
registrations. Hence a bottleneck of identity registration is image processing.
These are carried out in form of image preprocessing, image region extraction
by cropping, feature extraction using Principal Component Analysis (PCA) and
image compression using Discrete Cosine Transform (DCT). Other processing
includes filtering and histogram equalization using contrast stretching is
performed while enhancing the image as part of the analytical tool. Hence, this
research work presents a universal integration image forgery detection analysis
tool with image facial recognition using Back Propagation Neural Network (BPNN)
processor. The proposed designed tool is a multi-function smart tool with the
novel architecture of programmable error goal and light intensity. Furthermore,
its advance dual database increases the efficiency of a high-performance
application. With the fact that, the facial image recognition will always, give
a matching output or closest possible output image for every input image
irrespective of the authenticity, the universal smart GUI tool is proposed and
designed to perform image forgery detection with the high accuracy of 2% error
rate. Meanwhile, a novel structure that provides efficient automatic image
forgery detection for all input test images for the BPNN recognition is
presented. Hence, an input image will be authenticated before being fed into
the recognition tool.
