Advances in Spatial Databases: 5th International Symposium, by David J. Abel (auth.), Michel Scholl, Agnès Voisard (eds.)

By David J. Abel (auth.), Michel Scholl, Agnès Voisard (eds.)

This ebook constitutes the refereed complaints of the 5th foreign Symposium on Spatial Databases, SSD '97, held in Berlin, Germany, in July 1997.
The 18 revised complete papers awarded have been rigorously chosen from a complete of fifty five submissions. additionally integrated are keynote contributions. The papers are geared up in topical sections on spatial similarities, geo-algorithms, spatial constraint databases, spatial question processing, platforms, spatial information types and spatial entry methods.

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Vitabile et al. The proposed intelligent sensor is composed by a Sensor Acquisition Module (SAM) and a Sensor Processing Module (SPM). The first one is based on Hamster Secugen sensor [19] for fingerprint image acquisition. The second one is an FPGA based prototype implementing the whole fingerprint recognition chain. Modules have been installed on a standard workstation and their communication exploits standard PCI bus. R. R (False Rejection Rate) have been used to verify its performance. R. R. of 8%.

7×) over the same baseline SIMD array. z CAX reduces energy consumption from 80% to 89%, but MDMX reduces energy consumption from only 60% to 79% over the baseline version. z Moreover, CAX benefits from reduced pixel word storage in addition to greater concurrency. As a result, CAX outperforms MDMX for all the programs in area efficiency and energy efficiency. The area efficiency increases from 36% to 68% (an average of 52%) with CAX, but only 6% to 22% (an average of 13%) with MDMX. The energy efficiency increases from 35% to 77% (an average of 50%) with CAX, but only 2% to 24% (an average of 11%) with MDMX.

Experimental trials conducted on our sensor images show that they range around fixed values: 100, 250, 38, 5190, respectively. Fixing the above values, the equations to calculate the normalized pixel becomes more simple without the use of the square root and division operators: G(i, j) = M0 + (I(i, j) − M ) << 2 if I(i, j) ≥ M (2) G(i, j) = M0 − (I(i, j) − M ) << 2 if I(i, j) < M (3) where I(i,j) is the intensity of the pixel at the ith row and jth column and G(i,j) the relative normalized value.

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