To improve the face recognition
accuracy, we can consider the high quality with decreased compression rate.
In 2012, face recognition
is done in Discrete Wavelet Transform (DWT) domain which utilizes Haar wavelet and bi-orthogonal wavelet for feature extraction and uses Euclidean distance, L1 measure for classification and the Euclidean distance measure produce better recognition result as compared to L1 distance measure when Haar transform is used.
In 1960s First face recognition
algorithms was introduced in which geometric features were used for detection of face and recognition of a person .
Adrian believes that understanding how a bee's brain can process this information could lead to improvements in face recognition
PCA and LDA face recognition
methods involves matrix calculations with very high dimension.
At the first glance it might put our clients into confusion whether to go for the technology or not but if they are trying to search something advanced, with ultimate efficiency at an affordable rate then, biometric face recognition
system is what they are searching for," as explained by the business development executive of JustLook.
Ma continued, "This patent illustrates the continuing development of Titanium's technology and the company's commitment to producing the most efficient, user-friendly and accessible face recognition
devices available, allowing further security of Titanium's intellectual property and competitive edge in the marketplace.
For things like driver's license photos and mug shots, taken straight on with even lighting, face recognition
technology works fairly well.
Law enforcement has been learning how to use face recognition
and other biometrics for public safety and information security.
today announces the introduction of a Face Recognition
function that authenticates customers by sensing their facial features to increase mobile phone security.
The new evidence suggests that face recognition
doesn't require a big brain, he and his colleagues propose in the Dec.
The newly developed face recognition
function requires only about 280ms (ARM9/100MHz), the industry's fastest, from image acquisition to referencing.