2014 Fifth International Conference on Signal and Image Processing最新文献_第5页

Shape Representation and Classification through Pattern Spectrum and Local Binary Pattern -- A Decision Level Fusion Approach 基于模式谱和局部二值模式的形状表示与分类——一种决策级融合方法

2014 Fifth International Conference on Signal and Image Processing Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.41

B. H. Shekar, Bharathi Pilar

{"title":"Shape Representation and Classification through Pattern Spectrum and Local Binary Pattern -- A Decision Level Fusion Approach","authors":"B. H. Shekar, Bharathi Pilar","doi":"10.1109/ICSIP.2014.41","DOIUrl":"https://doi.org/10.1109/ICSIP.2014.41","url":null,"abstract":"In this paper, we present a decision level fused local Morphological Pattern Spectrum (PS) and Local Binary Pattern (LBP) approach for an efficient shape representation and classification. This method makes use of Earth Movers Distance (EMD) as the measure in feature matching and shape retrieval process. The proposed approach has three major phases: Feature Extraction, Construction of hybrid spectrum knowledge base and Classification. In the first phase, feature extraction of the shape is done using pattern spectrum and local binary pattern method. In the second phase, the histograms of both pattern spectrum and local binary pattern are fused and stored in the knowledge base. In the third phase, the comparison and matching of the features, which are represented in the form of histograms, is done using Earth Movers Distance (EMD) as metric. The top-n shapes are retrieved for each query shape. The accuracy is tested by means of standard Bulls eye score method. The experiments are conducted on publicly available shape datasets like Kimia-99, Kimia-216 and MPEG-7. The comparative study is also provided with the well known approaches to exhibit the retrieval accuracy of the proposed approach.","PeriodicalId":111591,"journal":{"name":"2014 Fifth International Conference on Signal and Image Processing","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125458188","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: 26

2014 Fifth International Conference on Signal and Image Processing Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.58

Harish Kumar, D. Chowdary

{"title":"Similarity Based Ranking of Query Results from Real Web Databases","authors":"Harish Kumar, D. Chowdary","doi":"10.1109/ICSIP.2014.58","DOIUrl":"https://doi.org/10.1109/ICSIP.2014.58","url":null,"abstract":"The information available in the World Wide Web is stored using many real Web databases (e.g. vehicle database). Accessing the information from these real Web databases has become increasingly important for the users to find the desired information. Web users search for the desired information by querying these Web databases, when the number of query results generated is large, it is very difficult for the Web user to select the most relevant information from the large result set generated. Users today, have become more and more demanding in terms of the quality of information that is provided to them while searching the Web databases. The most common solution to solve the problem involves ranking the query results returned by the Web databases. Earlier approaches have used query logs, user profiles and frequencies of database values. The problem in all of these techniques is that ranking is performed in a user and query independent manner. This paper, proposes an automated ranking of query results returned by Web databases by analyzing user, query and workload similarity. The effectiveness of this approach is discussed considering a vehicle Web database as an example.","PeriodicalId":111591,"journal":{"name":"2014 Fifth International Conference on Signal and Image Processing","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116854961","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: 0

Multilevel Framework for Summarization of Surveillance Videos 监控视频摘要的多级框架

2014 Fifth International Conference on Signal and Image Processing Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.48

C. Sujatha, A. R. Chivate, R. Tabib, U. Mudenagudi

引用次数: 7

Detection and Classification of Exudates Using K-Means Clustering in Color Retinal Images 基于k均值聚类的彩色视网膜图像渗出物检测与分类

2014 Fifth International Conference on Signal and Image Processing Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.25

G. G. Rajput, Preethi N. Patil

引用次数: 28

Identification of Annotations for Circuit Symbols in Electrical Diagrams of Document Images 文档图像电路图中电路符号标注的识别

2014 Fifth International Conference on Signal and Image Processing Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.53

Paramita De, Sekhar Mandal, Partha Bhowmick

引用次数: 6

Extracting the Liver and Tumor from Abdominal CT Images 从腹部CT图像中提取肝脏和肿瘤

2014 Fifth International Conference on Signal and Image Processing Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.24

M. Jayanthi, B. Kanmani

引用次数: 16

Image Encryption Using Chaotic Maps: A Survey 使用混沌映射的图像加密:综述

2014 Fifth International Conference on Signal and Image Processing Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.80

Priya R Sankpal, P A Vijaya

引用次数: 79

Features Based IUGR Diagnosis Using Variational Level Set Method and Classification Using Artificial Neural Networks 基于变分水平集的IUGR特征诊断和人工神经网络分类

2014 Fifth International Conference on Signal and Image Processing Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.54

Akhilraj V. Gadagkar, K. S. Shreedhara

{"title":"Features Based IUGR Diagnosis Using Variational Level Set Method and Classification Using Artificial Neural Networks","authors":"Akhilraj V. Gadagkar, K. S. Shreedhara","doi":"10.1109/ICSIP.2014.54","DOIUrl":"https://doi.org/10.1109/ICSIP.2014.54","url":null,"abstract":"Intrauterine growth restriction (IUGR) is the failure of the fetus to achieve his/her intrinsic growth potential. IUGR results in significant perinatal and long-term complications, including the development of insulin resistance/metabolic syndrome in adulthood [5]. Accurate and effective monitoring of fetal growth is one of the key component of prenatal care [3]. Ultrasound evaluation is considered the cornerstone of diagnosis and surveillance of the growth-restricted fetus [2]. Ultrasound measurements play a significant role in obstetrics as an accurate means for the estimation of the fetal age. Several parameters are used as aging parameters, the most important of which are the biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC) and femur length (FL). Serial measurement of these parameters over time is used to determine the fetal condition. Hence, consistency and reproducibility of measurements is an important issue. Consequently the automatic segmentation of anatomical structures in ultrasound imagery is a real challenge due to acoustic interferences (speckle noise) and artifacts which are inherent in these images. In this paper, a novel method is proposed for developing a Computer Aided Diagnosis (CAD) system for diagnosis and classification of IUGR foetuses. Diagnosis is performed by segmenting and extracting the required foetus features from an ultrasound image, using the Re-initialization free level set with Reaction Diffusion (RD) technique. An artificial neural network (ANN) classifier is developed, the features extracted are provided to the designed ANN model. The ANN then classifies normal and abnormal fetuses based on features provided.","PeriodicalId":111591,"journal":{"name":"2014 Fifth International Conference on Signal and Image Processing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114777255","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: 9

Fractal Dimension with Object Rotation: A Case Study with Glaucoma Eye 物体旋转的分形维数:以青光眼为例

2014 Fifth International Conference on Signal and Image Processing Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.22

Dharmanna Lamani, T. Manjunath, Ramegowda

{"title":"Fractal Dimension with Object Rotation: A Case Study with Glaucoma Eye","authors":"Dharmanna Lamani, T. Manjunath, Ramegowda","doi":"10.1109/ICSIP.2014.22","DOIUrl":"https://doi.org/10.1109/ICSIP.2014.22","url":null,"abstract":"The present research work explores application of perimeter method to determine fractal dimension for both glaucoma and non glaucoma eye. Fractal dimension is a real value treated as over simplified diagnostics parameter to determine earlier detection of glaucoma. A perimeter method is a well known method adopted to determine the fractal dimension of natural objects such as leaves and some biological organs. But no attempt has been made to consider importance of selecting an initial point and rotation of object to determine the fractal dimension. Hence this work explains procedure to determine fractal dimension considering rotation of object and selecting the initial point. The results obtained signify that rotation of object and selecting the initial point definitely influences fractal dimension for glaucoma eye, as found in this present case study. The fractal dimension found to be lesser for glaucoma eye because of attaining regular shape of optic cup and it is accounted by losses of optic nerve and blood vessels in different stages. The fractal dimension could be treated as an alternative method for manual deduction of glaucoma through cup-disc diameter ratio by ophthalmologist. The author concludes that as soon as eye attacked by glaucoma disease, fractal dimension starts to decrease leading to lesser values. The fractal dimension values found to be in the range of 1.4242 to 1.5986 for glaucoma and for non glaucoma 1.8643 to 2.3027. Hence fractal dimension as soon as it reaches 1.5986 (1.6) signifies earlier detection of glaucoma. The rotation of object also considered in the interval of 600 (00 to 3000) to determine the fractal dimension. One more finding is that transforming from irregular shape of optic cup to regular shape from non-glaucoma to glaucoma could be visualized in different stages of images, under section four.","PeriodicalId":111591,"journal":{"name":"2014 Fifth International Conference on Signal and Image Processing","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130154842","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: 12

ARM Based Implementation of Text-to-Speech (TTS) for Real Time Embedded System 基于ARM的实时嵌入式系统文本转语音(TTS)实现

2014 Fifth International Conference on Signal and Image Processing Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.36

A. Rawoof, Kulesh, K. C. Ray

引用次数: 13