A Comparative Study between the Support Vectors Machines and the K-Nearest Neighbors in the Handwritten Latin Numerals Recognition

보안공학연구지원센터(IJSIP) 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.2

In this paper we present a comparison between two methods of learning-classification, the first is the K-Nearest Neighbors (KNN) and the second is the Support Vectors Machines (SVM), these both methods are supervised and used for the recognition of handwritten Latin numerals that are extracted from the MNIST standard database. The recognition process organized as follows: in the pre-processing of numeral images, we exploited the thresholding, the centering and the normalization techniques, in the features extraction we have used the morphology mathematical, the zoning and the zig-zag methods. The classification methods include the K-Nearest Neighbors and the Support Vectors Machines. Our experiments results proved the highest test accuracies 93.13% and 86.50% respectively with SVM and KNN classifiers. The simulation results that we obtained demonstrate the SVM is more performing than the KNN in this recognition.

Analysis of Conformal Reflectarray on Cylindrical Surface

보안공학연구지원센터(IJSIP) 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.3

As the important case of conformal arrays, conformal arrays on cylindrical surfaces have been widely used in radar and communication systems. This paper explores the chances of designing conformal reflectarray on cylindrical platform. An extended array theory method is proposed in this paper for analyzing the radiation patterns of cylindrical conformal reflectarray. The radiation characteristics of conformal reflectarray on convex and concave cylindrical surfaces are studied, and the performances of the two cases are compared with planar cases. It is shown that the cylindrical conformal reflectarray can be a good candidate of high gain antennas for applications where a slightly curved conformal platform is available.

Improving brightness using Dynamic Fuzzy Histogram Equalization

보안공학연구지원센터(IJSIP) 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.2

This paper proposed brightness preserving dynamic fuzzy histogram equalization using triangular membership function which is the modified technique of histogram equalization. This modified technique, called Brightness Preserving Dynamic Fuzzy Histogram Equalization (BPDFHE), uses fuzzy statistics of digital images for their representation and processing in the fuzzy area which enables the technique to handle the approximation of gray level values in a better way for better presentation. This algorithm enhances image contrast as well as conserves the brightness very well. Some images are not available to excellent quality, so proposed Fuzzy algorithm can be used for image enhancement to improve the quality of the image.

Microwave Absorption Study of Nano Synthesized Strontium Ferrite Particles in X Band

보안공학연구지원센터(IJSIP) 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.10

Microwave ferrites require high coercivity for their use as microwave absorbers. Strontium hexaferrite is one of the best material due to its magnetic properties , high coercivity, large unilateral magnetic anisotropy and very low cost in comparison to others make it suitable for the use as microwave components specifically microwave absorber .Strontium nano hexa ferrites were successfully synthesized through chemical co-precipitation method. The synthesized nanostructure was characterized by X-Ray powder diffraction(XRD) and fourier transform infrared spectroscopy (FTIR).The XRD result shows the shift from amorphous to crystalline after the calcination of sample at 6000C.The behaviour of ferrite as microwave absorber was also studied for X band of frequencies.

Fuzzy Time Series Prediction Model and Application based on Fuzzy Inverse

보안공학연구지원센터(IJSIP) 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.10

This paper presents a forecast model of fuzzy time series prediction to study the prediction of enrollment. It takes the percentage of enrollment changes as the domain, constructs the inverse fuzzy number and predicts the enrollment of Qiong Zhou University from 2005 to 2013. Compared with the existing models, the mean square error and prediction error of the ameliorated model are smaller and the precision is higher. The authors get the better method to solve the prediction problem based on the inverse fuzzy prediction model.

A Review on Different Digital Watermarking Techniques

보안공학연구지원센터(IJSIP) 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.10

A digital watermark is a type of indicator covertly embedded in the noise tolerant signal such as an image or audio data. Digital watermarking is the method that embeds information known as a watermark into the multimedia object such that the watermark can be extracted or detected later to create an assertion about the object. Embedded watermark will permit recognizing the owner of the work hardware implementation. This idea is applicable for the digital video and audio also. Embedding a digital signal (image, video or video) with data which cannot be easily eliminated is called digital watermarking. Digital watermarks may be used to the authenticate the integrity or authenticity of the carrier signal or to display the identity of its owners Digital watermarking is used as a key result to create the document transferring protected from unlawful interferences. Digital watermark methods are used in numerous areas such as copyright owner identification, protection and broadcast monitoring. Digital watermarking is the processing of combined information into a digital signal. A watermark is a secondary image, which is overlaid on the host image, and provides a means of protecting the image. In this paper, aim is to present a survey of numerous methods on the basis of digital image watermarking. The digital watermarking method is becoming more important in this developing society of internet. The goal of this implementation is to survey the different techniques for Digital Watermarking.

A New Method of Active Power Measurement Based on Power Load Wiener-G Functionals Models

보안공학연구지원센터(IJSIP) 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.10

For the problem of electrical energy measurement could not be united under the condition of non-stationary distortion signals, in the paper, the functionals series was used to modeling the signals. Firstly, the Wiener kernel of nonlinear load was acquired; the output signal of nonlinear load was expressed using functionals series under the condition of sinusoidal excitation; and then, we used the wavelet transform to processed and acquired component of fundamental and distortion; and though the acquisition component of voltage and current, we analyzed the power flow of nonlinear load, and according the result of power flow, we proposed a new method of active power measurement. The simulation result shows that the result of theoretical analysis is the same as the new method, and the new method of electric energy measurement based on the functional series can achieve the reasonable electrical energy measurement.

Combined Forecasting Mode of Subgrade Settlement Based on Forecasting Availability and Real-coded Quantum Evolutionary Algorithm

보안공학연구지원센터(IJSIP) 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.10

Due to the normal forecasting methods for subgrade settlement using observation data have different explicabilities, and the predicting results has bigger volatility and lower accuracy. The Combined forecasting model of subgrade settlement based on forecasting availability and real-coded quantum evolutionary algorithm (RQEA) is put forward in this paper. At the first, according to the basic settlement law of subgrade and characteristics of settlement curve, the growth curve with the S-type characteristics are chosen as single forecasting model; Then, to get the weights of each single forecasting model, objective function is build on the basis of standard of forecasting availability maximization, and RQEA is employed to solve the objective function, and to construct the combined forecasting model of subgrade settlement. The result of engineering practice shows that the proposed method has better prediction accuracy and stability, and can meet engineering demand.

Design of Sliding Window Based Corner Detection Algorithm and Architecture for Image Mosaicing

보안공학연구지원센터(IJSIP) 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.3

A new Sliding Window Based Corner Detection Algorithm has been developed for image mosaicing. Using this algorithm, a new architecture suitable for VLSI implementation has also been designed. The proposed design incorporates a high degree of pipelining and parallelism and hence offers high throughputs. The color image mosaicing is achieved by first convolving an original image using a 3x3 sliding window followed by smoothening the image using median filters. The design has been coded in Verilog as per RTL coding guidelines. The algorithm has also been coded in Matlab in order to validate the hardware results. The Verilog design of the proposed architecture for image mosaicing has been implemented on Xilinx Spartan 6 xc6slx45-3fgg676 FPGA device. The design utilizes about 144,858 gates and the operating frequency is about 100 MHz. The design is capable of processing high resolution color pictures of sizes of up to 1600×1200 pixels in real time.

“Moving Object Tracking of Vehicle Detection” : A Concise Review

보안공학연구지원센터(IJSIP) 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.3

Vehicle detection and tracking applications play an important role for military and civilian applications such as in highway traffic surveillance control management and traffic planning.This paper presents a review on the various techniques of On-Road Vehicle detection systems that are based on motion model. In this paper a literature Survey of previous and recent works is presented on vision-based vehicle detection using sensors. Detecting the objects in the video and tracking their motion to identify their characteristics has been emerging as a demanding research area in the domain of Image Processing and Computer Vision. The traffic image analysis comprises of three parts: (1) Traffic Analysis (2) Motion Vehicle Detection and Segmentation Approaches and (3) Vehicle Tracking Approaches. In this survey, we have classified these methods into various groups, and these groups are providing a detailed description of various representation methods and find out their positive and negative aspects.