Punith Kumar M.B.,BGSIT |
Souvenir of the 2015 IEEE International Advance Computing Conference, IACC 2015 | Year: 2015
A rapid growth and development of life styles as well communicating media in recent years have changed considerably and called as information age. In this information age lot of changes were taken place in all domine like speed, data capacity, and distance of communication due to the development. Also hacking, tracing communicating bodies are also in place. The news channels and cameras are playing the major role in communication. The advancement in the TV news channel enabled by all the recent information occurs in the world available instantaneously as for as possible. This is due to moving line which is associated with a TV news channel but few treats the moving line text as disturbance where the above that watching above video so we plan to detect and extract the moving text from the news video using hybrid technology in association of edge and connected component detection. © 2015 IEEE.
Gayathri S.,SJCE |
Proceedings of 2014 International Conference on Contemporary Computing and Informatics, IC3I 2014 | Year: 2014
The performance of Fingerprint recognition system depends on minutiae which are extracted from raw fingerprint image. Often the raw fingerprint image captured from a scanner may not be of good quality, which leads to inaccurate extraction of minutiae. Hence it is essential to preprocess the fingerprint image before extracting the reliable minutiae for matching of two fingerprint images. Image enhancement technique followed by minutiae extraction completes the fingerprint recognition process. Fingerprint recognition process with a matcher constitutes Fingerprint recognition system ASIC implementation of image enhancement technique for fingerprint recognition process using Cadence tool is proposed. Further, the result obtained from hardware design is compared with that of software using MatLab tool. © 2014 IEEE.
Srinivas H.K.,P.A. College |
Srinivasan K.S.,EIT |
International Journal of Acoustics and Vibrations | Year: 2010
The vibration analysis of rotating machinery indicates the condition of potential faults such as unbalance, bent shaft, shaft crack, bearing clearance, rotor rub, misalignment, looseness, oil whirl and whip, and other malfunctions. More than one fault can occur in a rotor. This paper describes the application of an artificial neural network (ANN) and wavelet transform (WT) for the prediction of the effect of the combined faults of unbalance and shaft crack on the frequency components of the vibration signature of the rotating machinery. The experimental data of the frequency components and the corresponding root mean square (RMS) velocity (amplitude) data are used as inputs to train the ANN, which consists of a three-layered network. The ANN is trained using an improved multilayer feed forward back propagation Levenberg-Marquardt algorithm. In particular, the overall success rates achieved were 99.78% for unbalance, 99.81% for shaft crack, and 99.45% for the combined faults of unbalance and shaft crack. The wavelet transform approach enables instant to instant observation of different frequency components over the full spectrum. A new technique combining the WT with ANN performs three general tasks: data acquisition, feature extraction, and fault identification. This method is tested successfully for the individual and combined faults of unbalance and shaft crack at a success rate of 99.9%.
Shylashree N.,Research Scholar Faculty at RNSIT |
IEEE Region 10 Annual International Conference, Proceedings/TENCON | Year: 2016
In this paper, a high speed crypto-processor architecture for computing point multiplication for the elliptic curves defined over the prime fieldGF(p) is proposed. The proposed architecture uses amultiplierwhich utilizes parallel one's counters for accumulation of binary partial product bit. With the increase inspeed of multiplication, the speed of ECC point doubling and addition also increases. Also, the architecture takes advantage of an efficient projective coordinates system to convert GF(p) inversion needed in elliptic point operations into several multiplication steps. To increase the processor speed, efficient algorithms are used to compute modular multiplication, addition and subtraction, based on the argument that the speed of the Elliptic Curve Crypto-processor depends on how fast these arithmetic operations can be performed. The proposed architecture for computing 192-bit scalar multiplication for ECC can reach maximum frequency of 191 MHz and occupies 615 slices. It completes one 192-bit scalar multiplication in 676μs. © 2015 IEEE.
Gayathri S.,SJCE |
Lecture Notes in Electrical Engineering | Year: 2014
This paper presents FPGA implementation of minutiae extraction and false minutiae elimination for fingerprint image. A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Despite the widespread use of fingerprints, there is a little statistical theory on the uniqueness of fingerprint minutiae. A critical step in studying the statistics of fingerprint minutiae is to reliably extract minutiae from the fingerprint images. However, fingerprint images are rarely of perfect quality which requires image preprocessing techniques prior to minutiae extraction and false minutiae elimination. This will provide more reliable estimation of minutiae locations. Minutiae extraction and false minutiae elimination processes are implemented as a single block on FPGA. The FPGA configuration is generally specified using a hardware description language (HDL). © 2014 Springer India.