Notice Board: Call for Paper Vol. 8 Issue 10      Submission Start Date: September 30, 2021      Acceptence Notification Start: October 12, 2021      Submission End: October 18, 2021      Final MenuScript Due: October 22, 2021      Publication Date: October 31, 2021






Volume 2 Issue 3

Author Name
Chetan Patil, Pankaj Kawadkar
Year Of Publication
2015
Volume and Issue
Volume 2 Issue 3
Abstract
A license plate recognition system based on color features and hybrid classifier using feature selection technique is presented in this literature. The method presented here is based on a modified template-matching technique by the analysis of target color pixels to detect the location of a vehicle’s license plate. In this paper a hybrid method of number plate detection is proposed. The hybrid method of number plate detection is a combination of partial feature extraction technique and feature optimization using teacher learning based optimization algorithm. The proposed algorithm of number plate detection is based on feature selection and feature optimization process. The methodology and architecture of proposed system includes Partial Feature Extractor, Feature Selection, Support Vector Machine and Teacher Learning Based Optimization Algorithm. . For the selection of feature and optimization of used two different functions in TLBO algorithm, the selection of feature process satisfied
PaperID
2015/02/IJMERT/03/111

Author Name
Rakesh Verma, Rajendra Patel
Year Of Publication
2015
Volume and Issue
Volume 2 Issue 3
Abstract
Resource allocation is a major issue in computional grid computing. Due to limitation of resource and increasing rate of job faced a problem of maximum number of job failure. The maximum number of job failure decreases the perfromance of computional grid. The process of resouce and job allocation in computional grid have no standard method. The process of job allocation adapt first come first serivce. For the improvement of rsource allocation along with job used multi-cretria of ant colony optimization technique. The multi-cretria ant colony optimization technique failed in the case of large number of jobs in limited number of resource. For the improvement of job selection in multi-cretria ant colony optimization used TLBO selection process. The TLBO is new meta-heuristic function. In TLBO the population of new jobs like a student and selected job like a teacher for the process of ant colony optimzation technique. The modified process selection algorithm in ant colony optimization prid
PaperID
2015/02/IJMERT/03/109

Author Name
Gendal Lal, Sunil Gupta
Year Of Publication
2015
Volume and Issue
Volume 2 Issue 3
Abstract
Image data compression becomes still more important because of the fact that the transfer of uncompressed graphical data requires far more bandwidth and data transfer rate. So images are compressed. But in Quantization phase of compression process, there is some loss of data and hence some discontinuities are produced at the block boundaries. These are known as blocking artifacts. So it is necessary to remove or reduce these blocking artifacts. These filters are based on fuzzy rules. The main advantage of FIDRM is that it leaves the noise free pixels unchanged. SAWS (Signal Adaptive Weighted Sum) technique has also been implemented in which all the pixels of the given input image are modified. So experimental results shows the feasibility of new algorithm. A numerical measure such as PSNR and MSE show convincing results for grayscale images. The proposed algorithm is compared with SAWS technique which gives better results than that of SAWS technique. And it is observed that PSNR of pro
PaperID
2015/02/IJMERT/03/117



Notice Board :

Call for Paper
Vol. 8 Issue 10

Submission Start Date:
September 30, 2021

Acceptence Notification Start:
October 12, 2021

Submission End:
October 18, 2021

Final MenuScript Due:
October 22, 2021

Publication Date:
October 31, 2021