2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT)最新文献_第7页

Adaptive threshold based impulse detection for restoration of digital images 基于自适应阈值的数字图像脉冲检测

2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT) Pub Date : 2016-12-01 DOI: 10.1109/ICAECCT.2016.7942547

U. Ghanekar, R. Pandey

引用次数: 0

Identification and sorting of power quality disturbances using signal processing with GUI 基于图形用户界面的信号处理对电能质量干扰的识别和分类

2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT) Pub Date : 2016-12-01 DOI: 10.1109/ICAECCT.2016.7942556

A. Shinde, Sharad S. Jagtap, V. Puranik

{"title":"Identification and sorting of power quality disturbances using signal processing with GUI","authors":"A. Shinde, Sharad S. Jagtap, V. Puranik","doi":"10.1109/ICAECCT.2016.7942556","DOIUrl":"https://doi.org/10.1109/ICAECCT.2016.7942556","url":null,"abstract":"This paper based on the classification of the voltage signal on basis of quality. It can be achieved by various techniques according to applications and required accuracy. Feeder points at various locations of electrical substation play important role in reduction of noise from the supply voltage. However this is of less amount and considerable for general applications. In some industrial applications, this may cause a large loss due to the presence of noise. So for controlling the accuracy one can design a system which overcomes the problems arising due to noise. Using MATLAB software it is implemented for detection and identification. It has various algorithms like KNN, SVM and RBF. SVM is the powerful tool in MATLAB for identification and Classification of voltage signals, images as well as music signals. For this detection of signals, a database is applied for any type of transform. It is better to use wavelet transform for feature extraction purpose. This paper gives solution for identification and sorting of different noises in voltage signals using the pair of wavelet transform and SVM.","PeriodicalId":6629,"journal":{"name":"2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT)","volume":"17 1","pages":"60-63"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78669839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Evaluation of cooperative sensing for perfect reporting channels using dynamic detection threshold 基于动态检测阈值的完美报告通道协同感知评价

2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT) Pub Date : 2016-12-01 DOI: 10.1109/ICAECCT.2016.7942588

Deepa N. Reddy, Y. Ravinder

引用次数: 2

Error analysis in soil urea prediction based on RF spectroscopy 基于射频光谱的土壤尿素预测误差分析

2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT) Pub Date : 2016-12-01 DOI: 10.1109/ICAECCT.2016.7942591

S. Vernekar, Ingrid Nazareth, J. Parab, G. Naik

{"title":"Error analysis in soil urea prediction based on RF spectroscopy","authors":"S. Vernekar, Ingrid Nazareth, J. Parab, G. Naik","doi":"10.1109/ICAECCT.2016.7942591","DOIUrl":"https://doi.org/10.1109/ICAECCT.2016.7942591","url":null,"abstract":"With the growing concern for environmental pollution and shrinking land resources available for agriculture, the need for sustainable agriculture is increasing. Soil sensing plays an important role in sustainable agriculture as it provides an insight into the various soil properties thus enabling the farmer to adjust the inputs accordingly. The aim of the study is to design a soil sensor and analyze the errors in the prediction of a soil nutrient. The manuscript describes a new method for soil nutrient sensing using RF spectroscopy. The technique can predict soil urea content and is based on multivariate analysis using the PLSR (Partial Least Square Regression) mathematical tool. Eight different combinations of five important soil nutrients (Urea, Potash, Phosphate, Salt, and Lime) at varying concentration were used to develop multivariate block. The Urea prediction algorithm takes into account the effect of various other soil nutrients present in the sample. The results obtained show that the percentage error in prediction of urea is within the tolerable limits of +/−5% of the actual value, when other soil nutrient concentrations are varied below and above their normal values. The method can be extended for sensing multiple nutrients simultaneously by modifying the algorithm.","PeriodicalId":6629,"journal":{"name":"2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT)","volume":"71 1","pages":"244-246"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77397354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Neural network based gait phases of above knee prosthesis 基于神经网络的上膝假体步态相位分析

2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT) Pub Date : 2016-12-01 DOI: 10.1109/ICAECCT.2016.7942555

Vaishali Shirsath, M. Dongare

引用次数: 3

Design of gap-coupled variations of slotted and shorted 60° Sector microstrip antennas 开槽和短路60°扇形微带天线的间隙耦合设计

2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT) Pub Date : 2016-12-01 DOI: 10.1109/ICAECCT.2016.7942587

A. Deshmukh, Mohil Gala, S. Agrawal

引用次数: 0

Automatic joint detection and measurement of joint space width in arthritis 关节炎关节间隙宽度的自动检测与测量

2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT) Pub Date : 2016-12-01 DOI: 10.1109/ICAECCT.2016.7942626

S. Bhisikar, S. Kale

{"title":"Automatic joint detection and measurement of joint space width in arthritis","authors":"S. Bhisikar, S. Kale","doi":"10.1109/ICAECCT.2016.7942626","DOIUrl":"https://doi.org/10.1109/ICAECCT.2016.7942626","url":null,"abstract":"Arthritis is an inflammatory disease which causes erosion in bones or narrowing of joint space in various joints of the body. First symptom of this disease is seen in joints of hand finger and wrist joints thus making hand radiograph analysis extremely important. Lately Reading hand X-ray radiographic image to measure joint space width is very tedious and time consuming task for the radiologist since there are 14 joints in hand and also the structure of hand is complicated to carry out joint space width measurement and analysis. It has certain disadvantages like inaccuracy because of visual measurement and also variation from one reader to another, which can be overcome by automatic technique that can serve as a powerful aid for peoples suffering from disability due to pain, stiffness in joints. In this paper, Image processing based algorithm is developed to yield solution to two major problems joint detection and JSW measurement. The algorithm is divided into following steps, First image preprocessing is carried out using Gaussian filter. Second hand mask is extracted by separating foreground and background by using Otsu's binarization method. Third morphological thinning is applied to get thinned skeleton of binarized image. Fourth To detect joint location in original X-ray image Gabor filter is used. Fifth edge Finally of minimal joint space width is extracted and analyzed automatically. We have experimented 10 digital hand X-ray radiograph of resolution 2000pixels×2000pixels and calculated 120 readings of JSW of finger joints successfully.","PeriodicalId":6629,"journal":{"name":"2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT)","volume":"6 1","pages":"429-432"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74392947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Improved Context Dependent logo matching framework using FREAK method 改进了使用FREAK方法的上下文相关的标识匹配框架

2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT) Pub Date : 2016-12-01 DOI: 10.1109/ICAECCT.2016.7942614

D. R. Sonawane, S. Apte

{"title":"Improved Context Dependent logo matching framework using FREAK method","authors":"D. R. Sonawane, S. Apte","doi":"10.1109/ICAECCT.2016.7942614","DOIUrl":"https://doi.org/10.1109/ICAECCT.2016.7942614","url":null,"abstract":"Now days to prevent malicious use of original companies logos or identity, the automated image processing based frameworks are presented. The process of logo detection and recognition hence becoming the vital task for various applications. In this project we are presenting automated framework for logo detection using the real world logos images and its test image. Basically the working is that input query image is taken and big database of logos with goal of recognizing the logo in query image if any. Previously efficient method presented which outperform the existing method in terms of FRR and FPR. During this paper we are contributing by using RANSAC in which Fast Retina Keypoint (FREAK) descriptor is extracted for further matching and recognition process rather than using existing SIFT technique. The recent method for logo recognition and detection process is based on methodology of CDS (Context Dependent Similarity) which directly local features spatial context. Basically this CDS method using the SIFT method for initial keypoints extraction and then further matching process along with detection is done. The goal of our proposed CDS with RANSAC is to improve the recognition accuracy and to minimize the error rate performance. The RANSAC method is using FREAK technique for keypoints extraction which is superior as compared to SIFT.","PeriodicalId":6629,"journal":{"name":"2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT)","volume":"43 1","pages":"362-366"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80861479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Recognition of salient object 突出物体识别

2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT) Pub Date : 2016-12-01 DOI: 10.1109/ICAECCT.2016.7942599

Ms. Nikhila, Sayali Rawat

引用次数: 1

Voxel selection framework with signal decomposition for fMRI based brain activity classification 基于信号分解的体素选择框架用于fMRI脑活动分类

2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT) Pub Date : 2016-12-01 DOI: 10.1109/ICAECCT.2016.7942627

S. V. Raut, D. M. Yadav

引用次数: 0