A. Przybylak, P. Ślósarz, P. Boniecki, K. Koszela, K. Przybył, D. Wojcieszak, R. Szulc, A. Ludwiczak, K. Górna
{"title":"Marbling classification of lambs carcasses with the artificial neural image analysis","authors":"A. Przybylak, P. Ślósarz, P. Boniecki, K. Koszela, K. Przybył, D. Wojcieszak, R. Szulc, A. Ludwiczak, K. Górna","doi":"10.1117/12.2197027","DOIUrl":"https://doi.org/10.1117/12.2197027","url":null,"abstract":"This paper describes a part of research, whose goal was to develop an effective method to determine marbling classes of lamb carcasses, with the neural image analysis techniques. Current methods for identifying the degree of intramuscular fat level content are time consuming, require specialized expertise and often rely on subjective assessment based on predefined patterns. In this paper, authors proposes the use of neural model developed as a tool to assist evaluation of marbling.","PeriodicalId":273984,"journal":{"name":"CiiT international journal of digital image processing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128848707","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":"Detect ships using saliency in infrared images with sea-sky background","authors":"Fang Wu, Cheng-Fei Zhu, W. Xue","doi":"10.1117/12.2197021","DOIUrl":"https://doi.org/10.1117/12.2197021","url":null,"abstract":"Nowadays, ship detection in sea-sky background is not only useful in maritime visual surveillance, but also helpful in maritime search and rescue. Since ships are salient objects in infrared images with sea-sky background, we present a novel and effective algorithm based on saliency for ship detection in this situation. Our algorithm adopts global saliency, local saliency and background prior to generate saliency maps. Ships are finally segmented in saliency maps. Our algorithm is compared with four classic salient object detection algorithms. And experimental results show our algorithm outperforms the other four algorithms in qualitative and quantitative terms.","PeriodicalId":273984,"journal":{"name":"CiiT international journal of digital image processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125409240","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":"Design and implementation of face recognition system based on Windows","authors":"Min Zhang, Ting Liu, A. Li","doi":"10.1117/12.2196912","DOIUrl":"https://doi.org/10.1117/12.2196912","url":null,"abstract":"In view of the basic Windows login password input way lacking of safety and convenient operation, we will introduce the biometrics technology, face recognition, into the computer to login system. Not only can it encrypt the computer system, also according to the level to identify administrators at all levels. With the enhancement of the system security, user input can neither be a cumbersome nor worry about being stolen password confidential.","PeriodicalId":273984,"journal":{"name":"CiiT international journal of digital image processing","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121464353","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":"NoSQL: collection document and cloud by using a dynamic web query form","authors":"H. B. Abdalla, Jinzhao Lin, Guoquan Li","doi":"10.1117/12.2197093","DOIUrl":"https://doi.org/10.1117/12.2197093","url":null,"abstract":"Mongo-DB (from “humongous”) is an open-source document database and the leading NoSQL database. A NoSQL (Not Only SQL, next generation databases, being non-relational, deal, open-source and horizontally scalable) presenting a mechanism for storage and retrieval of documents. Previously, we stored and retrieved the data using the SQL queries. Here, we use the MonogoDB that means we are not utilizing the MySQL and SQL queries. Directly importing the documents into our Drives, retrieving the documents on that drive by not applying the SQL queries, using the IO BufferReader and Writer, BufferReader for importing our type of document files to my folder (Drive). For retrieving the document files, the usage is BufferWriter from the particular folder (or) Drive. In this sense, providing the security for those storing files for what purpose means if we store the documents in our local folder means all or views that file and modified that file. So preventing that file, we are furnishing the security. The original document files will be changed to another format like in this paper; Binary format is used. Our documents will be converting to the binary format after that direct storing in one of our folder, that time the storage space will provide the private key for accessing that file. Wherever any user tries to discover the Document files means that file data are in the binary format, the document's file owner simply views that original format using that personal key from receive the secret key from the cloud.","PeriodicalId":273984,"journal":{"name":"CiiT international journal of digital image processing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116605894","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}
Chien-Ping Liu, Ho-Ting Wu, Yun-Ting Chiang, Shieh-Chieh Chien, Kai-Wei Ke
{"title":"An energy saving mechanism of EPON networks for real time video transmission","authors":"Chien-Ping Liu, Ho-Ting Wu, Yun-Ting Chiang, Shieh-Chieh Chien, Kai-Wei Ke","doi":"10.1117/12.2197015","DOIUrl":"https://doi.org/10.1117/12.2197015","url":null,"abstract":"Modern access networks are constructed widely by passive optical networks (PONs) to meet the growing bandwidth demand. However, higher bandwidth means more energy consumption. To save energy, a few research works propose the dual-mode energy saving mechanism that allows the ONU to operate between active and sleep modes periodically. However, such dual-mode energy saving design may induce unnecessary power consumption or packet delay increase in the case where only downstream data exist for most of the time. In this paper, we propose a new tri-mode energy saving scheme for Ethernet PON (EPON). The new tri-mode energy saving design, combining the dual-mode saving mechanism with the doze mode, allows the ONU to switch among these three modes alternatively. In the doze mode, the ONU may receive downstream data while keeping its transmitter close. Such scenario is often observed for real time video downstream transmission. Furthermore, the low packet delay of high priority upstream data can be attained through the use of early wake-up mechanism employed in both energy saving modes. The energy saving and system efficiency can thus be achieved jointly while maintaining the differentiated QoS for data with various priorities. Performance results via simulation have demonstrated the effectiveness of such mechanism.","PeriodicalId":273984,"journal":{"name":"CiiT international journal of digital image processing","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127714064","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 spatiotemporal feature-based approach for facial expression recognition from depth video","authors":"Md. Zia Uddin","doi":"10.1117/12.2197074","DOIUrl":"https://doi.org/10.1117/12.2197074","url":null,"abstract":"In this paper, a novel spatiotemporal feature-based method is proposed to recognize facial expressions from depth video. Independent Component Analysis (ICA) spatial features of the depth faces of facial expressions are first augmented with the optical flow motion features. Then, the augmented features are enhanced by Fisher Linear Discriminant Analysis (FLDA) to make them robust. The features are then combined with on Hidden Markov Models (HMMs) to model different facial expressions that are later used to recognize appropriate expression from a test expression depth video. The experimental results show superior performance of the proposed approach over the conventional methods.","PeriodicalId":273984,"journal":{"name":"CiiT international journal of digital image processing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127796444","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}
R. Izmailov, D. Bassu, Allen McIntosh, Linda Ness, D. Shallcross
{"title":"Application of multi-scale singular vector decomposition to vessel classification in overhead satellite imagery","authors":"R. Izmailov, D. Bassu, Allen McIntosh, Linda Ness, D. Shallcross","doi":"10.1117/12.2196925","DOIUrl":"https://doi.org/10.1117/12.2196925","url":null,"abstract":"Creation and selection of relevant features for image classification is a process requiring significant involvement of domain knowledge. It is thus desirable to cover at least part of that process with semi-automated techniques capable of discovering and visualizing those geometric characteristics of images that are potentially relevant to the classification objective. In this work, we propose utilizing the multi-scale singular value decomposition (MSVD), which can be efficiently run on large high-dimensional datasets. We apply this technique to create a multi-scale representation of overhead satellite images of various types of vessels, with the objective of identifying those types. We augment the original set of pixel data with features obtained by applying the MSVD to multi-scale patches of the images. The result is then processed using a linear Support Vector Machine (SVM) algorithm. The classification rule obtained is significantly better than the one based on the original pixel space. The generic nature of the MSVD mechanism and standard mechanisms used for classification (SVM) suggest a wider utility of the proposed approach.","PeriodicalId":273984,"journal":{"name":"CiiT international journal of digital image processing","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133222081","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":"Use of the self-organizing feature map to diagnose abnormal engineering change","authors":"Ruei-Shan Lu, Zhi-Ting Wu, K. Peng, Tai-Yi Yu","doi":"10.1117/12.2197118","DOIUrl":"https://doi.org/10.1117/12.2197118","url":null,"abstract":"This study established identification manners with self-organizing feature map (SOM) to achieve the goal of monitoring Engineering Change (EC) based on historical data of a company that specializes in computers and peripherals. The product life cycle of this company is 3–6 months. The historical data were divided into three parts, each covering four months. The first part, comprising 2,343 records from January to April (the training period), comprise the Control Group. The second and third parts comprise Experimental Groups (EG) 1 and 2, respectively. For EG 1 and 2, the successful rate of recognizing information on abnormal ECs was approximately 96% and 95%, respectively. This paper shows the importance and screening procedures of abnormal engineering change for a particular company specializing in computers and peripherals.","PeriodicalId":273984,"journal":{"name":"CiiT international journal of digital image processing","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133019285","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}
P. Boniecki, H. Piekarska-Boniecka, K. Koszela, M. Zaborowicz, K. Przybył, D. Wojcieszak, Z. Zbytek, A. Ludwiczak, A. Przybylak, A. Lewicki
{"title":"Neural classifier in the estimation process of maturity of selected varieties of apples","authors":"P. Boniecki, H. Piekarska-Boniecka, K. Koszela, M. Zaborowicz, K. Przybył, D. Wojcieszak, Z. Zbytek, A. Ludwiczak, A. Przybylak, A. Lewicki","doi":"10.1117/12.2197029","DOIUrl":"https://doi.org/10.1117/12.2197029","url":null,"abstract":"This paper seeks to present methods of neural image analysis aimed at estimating the maturity state of selected varieties of apples which are popular in Poland. An identification of the degree of maturity of selected varieties of apples has been conducted on the basis of information encoded in graphical form, presented in the digital photos. The above process involves the application of the BBCH scale, used to determine the maturity of apples. The aforementioned scale is widely used in the EU and has been developed for many species of monocotyledonous plants and dicotyledonous plants. It is also worth noticing that the given scale enables detailed determinations of development stage of a given plant. The purpose of this work is to identify maturity level of selected varieties of apples, which is supported by the use of image analysis methods and classification techniques represented by artificial neural networks. The analysis of graphical representative features based on image analysis method enabled the assessment of the maturity of apples. For the utilitarian purpose the ”JabVis 1.1” neural IT system was created, in accordance with requirements of the software engineering dedicated to support the decision-making processes occurring in broadly understood production process and processing of apples.","PeriodicalId":273984,"journal":{"name":"CiiT international journal of digital image processing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116227834","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}
Chunhua Li, Zhiming Cui, Pengpeng Zhao, Jian Wu, Jie Xin, Tianxu He
{"title":"Improving ontology matching with propagation strategy and user feedback","authors":"Chunhua Li, Zhiming Cui, Pengpeng Zhao, Jian Wu, Jie Xin, Tianxu He","doi":"10.1117/12.2197167","DOIUrl":"https://doi.org/10.1117/12.2197167","url":null,"abstract":"Markov logic networks which unify probabilistic graphical model and first-order logic provide an excellent framework for ontology matching. The existing approach requires a threshold to produce matching candidates and use a small set of constraints acting as filter to select the final alignments. We introduce novel match propagation strategy to model the influences between potential entity mappings across ontologies, which can help to identify the correct correspondences and produce missed correspondences. The estimation of appropriate threshold is a difficult task. We propose an interactive method for threshold selection through which we obtain an additional measurable improvement. Running experiments on a public dataset has demonstrated the effectiveness of proposed approach in terms of the quality of result alignment.","PeriodicalId":273984,"journal":{"name":"CiiT international journal of digital image processing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124467184","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}