B. Sowmya, A. Thirumaran, R. Aravindh, Avr. Adhithiya Prasad
{"title":"Land cover classification using Adaptive Resonance Theory-2","authors":"B. Sowmya, A. Thirumaran, R. Aravindh, Avr. Adhithiya Prasad","doi":"10.1109/ICECCT.2011.6077074","DOIUrl":"https://doi.org/10.1109/ICECCT.2011.6077074","url":null,"abstract":"This paper describes the task of land cover classification using Adaptive Resonance Theory 2 (ART 2). Adaptive resonance theory 2 has been used to segment the satellite image. Image segmentation refers to the partition of pixels into homogeneous classes so that items in the same class are as similar as possible and pixels in different classes are as dissimilar as possible. The most basic attribute for segmentation is image intensity for a monochrome image and color components for a color image. Since there are more than 16 million colors available in any given image and it is difficult to analyze the image on all of its colors, the likely colors are grouped together by image segmentation ART 2 has been used for image segmentation. The RGB values of each pixel are found. Depending on the spectral value, the pixels are classified as urban area, bare soil, forest & vegetation and water regions by ART 2.","PeriodicalId":158960,"journal":{"name":"2011 International Conference on Electronics, Communication and Computing Technologies","volume":"982 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132967302","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":"Eye features normalization and face emotion detection for human face recognition","authors":"D. Jagadiswary, G. Appasami, S. Rajesh","doi":"10.1109/ICECCT.2011.6077071","DOIUrl":"https://doi.org/10.1109/ICECCT.2011.6077071","url":null,"abstract":"Iris recognition is very essential in human identification. It gets more attention in human face recognition. There are several proposals to develop systems that operate in the visible wavelength and in less constrained environments. These imaging conditions engender acquired noisy artefacts that lead to severely degraded images, making iris segmentation a major issue. Having observed that existing iris segmentation methods tend to fail in these challenging conditions, we present a segmentation method that can handle degraded images acquired in less constrained conditions. we offer the following contributions: first to consider the sclera the most easily distinguishable part of the eye in degraded images, then a new type of feature that measures the proportion of sclera in each direction and is fundamental in segmenting the iris, and finally to run the entire procedure in deterministically linear time in respect to the size of the image, making the procedure suitable for real-time applications. In this paper we discussed eye features normalisation and face detection for human identification.","PeriodicalId":158960,"journal":{"name":"2011 International Conference on Electronics, Communication and Computing Technologies","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117182561","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":"Employee monitoring & HR management using RFID","authors":"S. Srinivasan, H. Ranganathan, R. Srivel","doi":"10.1109/ICECCT.2011.6077069","DOIUrl":"https://doi.org/10.1109/ICECCT.2011.6077069","url":null,"abstract":"RFID is a term which designates a system where people or objects transmit their identification over radio frequencies. In earlier technologies, the labels or tags had to be scanned manually to capture the identity of the person/object. RFID, however, doesn't require manual scanning. An RFID system is generally made up of several readers with antennas which emit radio signals and capture back the signals emitted by tag. The context of our employee tracking application is we will provide each employee with RFID tag which correlates with two or more RFID reader which is placed inside the campus/office premises. The tag is activated with RF energy from the antennas that are placed in the chair of employees and it extracts information from the tag. Each tag has a unique ID. RFID reader converts the radio waves returned from the tag into a form that can be passed on to the controller. The data is updated at regular intervals in the host computer using wireless zigbee protocol (802.15.4). The delay is programmed using microcontroller. The performance of each employee is determined with the help of application software Visual Basic.","PeriodicalId":158960,"journal":{"name":"2011 International Conference on Electronics, Communication and Computing Technologies","volume":"188 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127667231","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}