Free facial recognition software for windows

WareSeeker Editor

Iris Recognition System 1 is created as a professional mathematics related tool. Iris Recognition System Matlab Source Code. The iris of each eye is unique. No two irises are alike in their mathematical detail--even between identical twins and triplets or between one's own left and right eyes. Unlike the retina, however, it is clearly visible from a distance, allowing easy image acquisition without intrusion.

The iris remains stable throughout one's lifetime, barring rare disease or trauma. The random patterns of the iris are the equivalent of a complex human barcode, created by a tangled meshwork of connective tissue and other visible features. The iris recognition process begins with video-based image acquisition that locates the eye and iris. Matlab Image Processing Toolbox is required.

With custom defined gestures via the SVG format, Gesture Recognition attempts to compare your hand drawings with those it knows.
Gesture Recognition will inform you of how close you come to a certain figure.
One of the main difficulties for this demo was deciding on a gesture file format. I needed something that was both easy for the neural net to learn and for the end user to create custom gestures. I concluded that SVG was perfect for the situation. Any SVG file placed in the Data/Gestures folder will be loaded on startup. So just plug your custom gestures in there.

DCT-Based Iris Recognition 1.0 is one of the most convenient and easy to use programs for iris matching using zero crossings of a Discrete Cosine Transform (DCT) as a means of feature extraction for later classification. The DCT of a series of averaged overlapping patches are taken from normalized iris images and a small subset of coefficients is used to form subfeature vectors. Iris codes are generated as a sequence of many such subfeatures, and classification is carried out using a weighted Hamming distance metric.

Hybrid Iris Recognition 1.0 is an advise mathematic program for Windows. The use of biometric signatures, instead of tokens such as identification cards or computer passwords, continues to gain increasing attention as an efficient means of identification and verification of individuals for controlling access to secured areas, materials, or systems and a wide variety of biometrics has been considered over the years in support of these challenges. Iris recognition is especially attractive due to the stability of the iris texture patterns with age and health conditions. Iris image segmentation and localisation is a key step in iris recognition and plays an essential role the accuracy of matching.

Face Recognition in Fourier Space 1 is an easy-to-use and comprehensible face recognition system that is designed based on an analysis of faces via their Fourier spectra. Face Recognition in Fourier Space - Matlab source code. Recognition is done by finding the closest match between feature vectors containing the Fourier coefficients at selected frequencies. The introduced method compares favorably to three other competing approaches implemented on the same database.

Requirements:

• Windows 3.x/95/98/Me/NT/2000/XP/2003 Server/Vista
• Matlab

Font Image Recognition Routine will allow you to build vector file out of 100x100 pixels 24-bit color depth bitmap image of freehand drawn fonts.
Comparison of two different vector files states same/different font drawing. This routine is aimed help PDA users write/input text in an easier way.
This routine creates a vector shape sequence file (using -i switch) out of an 100x100 pixels 24 bit colour depth black and white image representing a character truetype image (font) or character freehand drawing.
Then using the -c switch the two index files derived from two different images are compared and graphics matching result is displayed.
At present the routine builds shape vectors on black/white bitmaps, it does not support different resolution nor colors/color depth. This development is aimed for PDA users using easier ways for text input.