Draft1

=It looks Very Well... Congrats ! ! = = __PATTERN RECOGNITION AND FINGERPRINT RECOGNITION__ = = **Introduction:** =

__Pattern recognition techniques__ are concerned with the theory and algorithms of putting abstract objects, e.g., measurements made on physical objects, into categories. Typically the categories are assumed to be known in advance, although there are techniques to learn the categories (clustering). Methods of pattern recognition are useful in many applications such as information retrieval, data mining, document image analysis and recognition, computational linguistics, forensics, biometrics and bioinformatics.

For example, the application of pattern recognition techniques is used, commonly, in fingerprint recognition, handwriting recognition and handwriting verification.

__The Fingerprint:__ 

A smoothly flowing pattern formed by alternating crests (ridges) and troughs (valleys) on the palmer aspect of hand is called a palmprint. Formation of a palmprint depends on the initial conditions of the embryonic mesoderm from which they develop. The pattern on pulp of each terminal phalanx is considered as an individual pattern and is commonly referred to as a //fingerprint//. A fingerprint is believed to be unique to each person (and each finger). Fingerprints of even identical twins are different.

A number of approaches to fingerprint classification have been developed. Some of the earliest approaches did not make use of the rich information in the ridge structures and exclusively depended on the orientation field information. Although fingerprint landmarks provide very effective fingerprint class clues, methods relying on the fingerprint landmarks alone may not be very successful due to lack of availability of such information in many fingerprint images and due to the difficulty in extracting the landmark information from the noisy fingerprint images. As a result, the most successful approaches need to (i) supplement the orientation field information with ridge information; (ii) use fingerprint landmark information when available but devise alternative schemes when such information cannot be extracted from the input fingerprint images; and (iii) use reliable structural/syntactic pattern recognition methods in addition to statistical methods.

We summarize a method of classification which takes into consideration the above mentioned design criteria that has been tested on a large database of realistic fingerprints to classify fingers into five major categories: right loop, left loop, arch, tented arch, and whorl. Loops make up nearly 2/3 of all fingerprints, whorls are nearly 1/3, and perhaps 5-10% are arches.

**Figure 1: A Method of Classification.** 

The fingerprint shown in Figure 2 below is a right loop. 

**. Figure 2**  

Hi Mariale! I think your draft is really good, and I have some opinions to see if you agree with me. I think you need to explain more about how fingerprint recognition is used, I mean the process, machines or something like that. Also what are the advantages and disadvantages of this technique and I think the mathematics part is really important, meaning that you should explain how math is related to making the comparison between two fingerprints. I noticed that there is a lot of technical vocabulary in your text (there are a lot of words that I had to search to see what they ment) and I don't know if that's ok but I leave it to you.