{"title":"Segmentation of plant disease spots using automatic SRG algorithm: a look up table approach","authors":"R. K. Sarkar, A. Pramanik","doi":"10.1109/ICACEA.2015.7194375","DOIUrl":"https://doi.org/10.1109/ICACEA.2015.7194375","url":null,"abstract":"Image segmentation is the key component of identifying plant leaf diseases. Most of the available techniques for leaf disease segmentation use grayscale values. In this paper, an automatic seeded region growing (SRG) algorithm for coloured images proposed by Y. Shih and S. Cheng is modified for segmentation of plant leaf diseases. The colour difference between adjacent regions is computed using Euclidean distance metric in the algorithm. This paper proposes a novel two dimensional look up table for labeling the neighbours for region merging. The look up table is created by traversing the image vertically and horizontally and any change in the labels of pixel is noted in the table. The incorporation of the table helps in better organization in region merging step and helps in further segmentation of the image. It must be noted that the performance of coloured image segmentation largely depends on the colour space chosen. The algorithm is first implemented in the YCbCr colour space and then implemented in other colour spaces like YCgCr, CIELAB and RGB to check for the best performance of the segmentation algorithm. Experimental results show that the SRG algorithm along with the proposed modification for region merging give good results in the YCbCr compared to other colour spaces for plant leaf disease segmentation.","PeriodicalId":202893,"journal":{"name":"2015 International Conference on Advances in Computer Engineering and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131006684","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}
{"title":"Recent advancements in requirement elicitation and prioritization techniques","authors":"Nikita Garg, P. Agarwal, Shadab Khan","doi":"10.1109/ICACEA.2015.7164702","DOIUrl":"https://doi.org/10.1109/ICACEA.2015.7164702","url":null,"abstract":"Requirement Elicitation identify as one of the most crucial knowledge intensive activities of software development. Most of the system fails due to use of wrong elicitation practice. A requirement is defined as a demand or needs. A System may have a dozen to thousands of requirement. Without the Elicitation technique it is impossible to find out the requirement and need of developing system. After Elicitation Technique we need to prioritize their requirements. This Research paper is based on understanding technique and their usage in the real time applications by using the Elicitation Technique and Prioritization Technique we know that it is important for knowing the need of the stakeholder so that the system developer can get a clear view of requirement for the developing system.","PeriodicalId":202893,"journal":{"name":"2015 International Conference on Advances in Computer Engineering and Applications","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132662332","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}
{"title":"Performance analysis of training algorithms of multilayer perceptrons in diabetes prediction","authors":"Sumi Alice Saji, K. Balachandran","doi":"10.1109/ICACEA.2015.7164695","DOIUrl":"https://doi.org/10.1109/ICACEA.2015.7164695","url":null,"abstract":"Artificial Intelligence plays a vital role in developing machines or software that can create intelligence. Artificial Neural Networks is a field of neuroscience which contributes tremendous developments in Artificial Intelligence. This paper focuses on the study of performance of various training algorithms of Multilayer Perceptrons in Diabetes Prediction. In this study, we have used Pima Indian Diabetes data set from UCI Machine Learning Repository as input dataset. The system is implemented in MatlabR2013. The Pima Indian Diabetes dataset consists of about 768 instances. The input data is the patient history and the target output is the prediction result as tested positive or tested negative. From the performance analysis, it was observed that out of all the training algorithms, Levenberg-Marquardt Algorithm has given optimal training results.","PeriodicalId":202893,"journal":{"name":"2015 International Conference on Advances in Computer Engineering and Applications","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128919383","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}
Vinita Chauhan, Vineet Chauhan, Hema Kashyap, Vikas Singh
{"title":"Comprehensive set of mutation operators for the determination of adequacy of test set","authors":"Vinita Chauhan, Vineet Chauhan, Hema Kashyap, Vikas Singh","doi":"10.1109/ICACEA.2015.7164856","DOIUrl":"https://doi.org/10.1109/ICACEA.2015.7164856","url":null,"abstract":"A mutation system possess the extensive theoretical components called mutation operators that are designed to evaluate the effectiveness of fault detection. Mutation testing of a software system rely extremely on the kinds of faults detected that the mutation operators are designed to represent. Therefore, the quality of the mutation operators is very significant to mutation testing. The interaction mutation provides criteria for the determination of the adequacy of tests generated for the software system. It helps in determining whether the test cases that have been created effectively detect all the possible faults in the software with sufficient mutation operators. The types of faults that the mutation operators are designed to represent plays a key role in determining the effectiveness of a test case. Therefore, the mutation testing heavily relies on the quality of the mutation operators. This work targets this issue by providing a set of additional mutation operators for creating mutants of the source code of few modules of an existing software system.","PeriodicalId":202893,"journal":{"name":"2015 International Conference on Advances in Computer Engineering and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127824730","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}
{"title":"Algorithms for clustering XML documents: A review","authors":"Shagun Gulati, Geetika Munjal","doi":"10.1109/ICACEA.2015.7164772","DOIUrl":"https://doi.org/10.1109/ICACEA.2015.7164772","url":null,"abstract":"This paper provides a brief survey of various algorithms that are widely being used for the clustering of XML (Extensible Markup Language) documents. The scalable integration techniques and algorithms, like XClust algorithm, S-GRACE algorithm, XProj algorithm, XCleaner algorithm and many more, are being developed for the growing number of data sources of XML documents. These techniques have been used for reduction in many problems of clustering but still we can find the problem of clustering complexity which is being discussed here and the technique to overcome that is being thought to be taken up as the future work.","PeriodicalId":202893,"journal":{"name":"2015 International Conference on Advances in Computer Engineering and Applications","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115786360","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}
Bharti Nagpal, Nanhay Singh, N. Chauhan, Radhika Murari
{"title":"A survey and taxonomy of various packet classification algorithms","authors":"Bharti Nagpal, Nanhay Singh, N. Chauhan, Radhika Murari","doi":"10.1109/ICACEA.2015.7164675","DOIUrl":"https://doi.org/10.1109/ICACEA.2015.7164675","url":null,"abstract":"Routers can also function as firewalls and perform various operations on the incoming and outgoing packets. In case when all the packets share common header characteristics, it is termed as a packet flow. In order to classify a packet, routers perform a lookup on a classifier table using one or more fields from the packet header to classify the packet into its corresponding flow. A classifier is a set of rules which identify each flow and the appropriate actions to be taken for any packet belonging to that flow. The paper examines the problem of packet classification and various proposed techniques for the same.","PeriodicalId":202893,"journal":{"name":"2015 International Conference on Advances in Computer Engineering and Applications","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115067571","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}
Shivani Saluja, T. Bedwal, Deepti Rana, Radhika Tayal
{"title":"Non text eradication from degraded and non degraded videos and images","authors":"Shivani Saluja, T. Bedwal, Deepti Rana, Radhika Tayal","doi":"10.1109/ICACEA.2015.7164806","DOIUrl":"https://doi.org/10.1109/ICACEA.2015.7164806","url":null,"abstract":"Text Segmentation of text from degraded document images is a very complex task due to high mutation between the document background and foreground region. Automatic text extraction is one of the basic feature required for content-based video indexing, automated indexing, automated annotation, structuring and retrieval tasks. Text detection from videos demands conversion of entire video into smaller framesets. Further the framesets are binarized to ease the extraction procedure. This in turn is followed by application of detection procedure on the static frames generated from the video. Text detection can lead to extraction of both superficial and embedded text. Embedded text will be the focus of this research paper because a part of the information depicted in the superficial text is already present in the embedded region. The cycle would start from conversion of dynamic video into static frames, followed by application of filters for noise removal, use of basic morphological operation like dilation and erosion, creation of bounding boxes around the textual content and finally removal of the non text region in such a manner that only the textual region in enhanced. The enhanced textual region is retained while the non textual content is eliminated.","PeriodicalId":202893,"journal":{"name":"2015 International Conference on Advances in Computer Engineering and Applications","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123427191","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}
{"title":"A review on analysis of EEG signals","authors":"Jasjeet Kaur, Amanpreet Kaur","doi":"10.1109/ICACEA.2015.7164844","DOIUrl":"https://doi.org/10.1109/ICACEA.2015.7164844","url":null,"abstract":"Electroencephalography (EEG) enlighten about the state of the brain i.e. about the electrical bustle going on in the brain. The electrical activity measured as voltage at different points of brain act as basis of EEG. These signals are generally time-varying and non-stationary in nature. These signals can be scrutinized using various signal processing techniques. In this paper, few statistical approaches to analyze EEG data are conversed.","PeriodicalId":202893,"journal":{"name":"2015 International Conference on Advances in Computer Engineering and Applications","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125784352","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}
{"title":"Neural network based group authentication using (n, n) secret sharing scheme","authors":"S. K. Narad, P. Chavan","doi":"10.1109/ICACEA.2015.7164739","DOIUrl":"https://doi.org/10.1109/ICACEA.2015.7164739","url":null,"abstract":"In recent days, usage of internet is increasing so; authentication becomes the most important security services for communication purpose. Keeping this into consideration, there is need of robust security services and schemes. This paper proposes Group Authentication authenticates all users at a time belonging to the same group. The (n, n) Group Authentication Scheme is very efficient since it authenticates all users if they are group members. If they are nonmembers, then it may be used as a preprocess and apply authentication before and it identifies the non-members. Also, if any of the users present in group authentication is absent then the group is not authenticated at all, as each share is distributed to each user. It results in best authenticated system as the Group Authentication is implemented with Neural Network. So it becomes complicated for hackers to hack each neuron in a neural network. The Neural Network based group authentication is specially designed for applications performing group activities using Shamir Secret Sharing Scheme.","PeriodicalId":202893,"journal":{"name":"2015 International Conference on Advances in Computer Engineering and Applications","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125787882","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}
{"title":"Mobility management in heterogeneous wireless networks based on IEEE 802.21 framework","authors":"Vimal Kumar, A. Gupta, Satish Kumar, Vipin Kumar","doi":"10.1109/ICACEA.2015.7164839","DOIUrl":"https://doi.org/10.1109/ICACEA.2015.7164839","url":null,"abstract":"Wireless and mobile networks are evolving very rapidly. The mobile nodes in the wireless networks are having multiple interfaces with different radio access technologies (RATs) which are having different capabilities, cost and performance ratio. The use of non-PC based portable devices is increasing due to their flexible usage. The wireless and mobile network which is formed by these non-PC and PC based devices is heterogeneous in nature and these networks are co-located. Multiple interfaces can be included in the mobile device by using separate hardware and software modules. A mobile user wants to be Always Best Connected (ABC) as per its various requirements and availability in a particular environment. When a mobile node leaves the current network and joins the other network, a handover operation is needed and performed. The Handover operation is used to achieve seamless mobility and is of two types, first is in between same RATs and second is in between different RATs. For seamless and smooth handover operations across heterogeneous networks, IEEE has published a standard, named as IEEE 802.21. This paper presents a comprehensive description on the issues and challenges for achieving the seamless mobility in a heterogeneous environment. Apart from this, we also present the description of services provided by IEEE 802.21 standard and related vertical handover schemes to realize seamless mobility in heterogeneous network.","PeriodicalId":202893,"journal":{"name":"2015 International Conference on Advances in Computer Engineering and Applications","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126162298","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}