摘要(英) |
The valleys and ridges of a finger occurs total internal reflection and scattering phenomenon, and then images and focus on the sensor with the imaging lens. According to total internal reflection and scattering result in power of light energy, distinguish out the ridges and valleys of a finger. Finally, the image of fingerprint is captured with a sensor.
In order to analyze structure effectively and quickly, we regard the valleys as the point sources. In this thesis, with the model of this concept is called “Approximate Point Model”. Actually, take place valleys of total internal reflection is line sources and is not point sources. Therefore, the concept of line source with the model in this paper is called “Similar Fingerprint Model”.
We use Approximate Point Model and Similar Fingerprint Model to simulate four kinds of fingerprint identification by the optical commercial software, ASAP. Four kinds of optical modules are Traditional Type, Modified Type, New Type 1 and New Type 2 respectively. In order to analyze the difference of imaging quality is between Traditional Type, Modified Type, New Type 1 and New Type 2. We use three items to estimate the imaging quality. Three items are distortion, relative distortion and image contrast.
The Modified Type is better than Traditional Type. Because of the image contrasts are 0.56 and 0.32 at +7.5 mm and -7.5 mm in Traditional Type, and the image contrasts are 0.65 and 0.64 at +7.5 mm and -7.5 mm in Modified Type. The minimum image contrast is 0.50 in New Type1 and 0.72 in New Type2. According to the result we can know New Type2 is better than New Type1.
Design final is tolerance analysis. We first use Taguchi Method and ISO10110 to execute tolerance analysis. We can know relation of each factor influence image contrast. It can help us to correct the value of tolerance. And we modify New Type 1 and New Type 2 to attain better image contrast finally. |
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