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Swarnalatha P

Bio: Swarnalatha P is an academic researcher. The author has contributed to research in topics: Depth map & Satellite imagery. The author has an hindex of 1, co-authored 1 publications receiving 7 citations.

Papers
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01 Jan 2014
TL;DR: In this article, the first phase of pre-processing is used to make the satellite images free from such errors and then the image is reconstructed with depth dimension/depth map generation for the anaglyph image for better interpretation of satellite imagery.
Abstract: The Images obtained through remote sensing systems are not often sufficient for high precision applications due to various distortions. The distortions can be due to errors like geometric errors, etc. Also multi-date satellite images of the same area under different conditions are difficult to compare because of change in atmospheric propagation, sensor response and illuminations. Keeping these points in view, in this paper, we deal with the first phase of pre-processing and we make the satellite images free from such errors and use clustering techniques With Geometric Correction (WGC) and Without Geometric Correction (WOGC) applied to the satellite images using our proposed algorithm. Finally, the image is reconstructed with depth dimension/depth map generation for the anaglyph image for better interpretation of satellite imagery. We have made experimental analysis of our algorithm using suitable satellite images and found the results to be very encouraging.

7 citations


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01 Jan 2016
TL;DR: The remote sensing and image interpretation is universally compatible with any devices to read and is available in the digital library an online access to it is set as public so you can get it instantly.
Abstract: Thank you very much for downloading remote sensing and image interpretation. As you may know, people have look hundreds times for their favorite novels like this remote sensing and image interpretation, but end up in malicious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they are facing with some malicious virus inside their computer. remote sensing and image interpretation is available in our digital library an online access to it is set as public so you can get it instantly. Our book servers spans in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the remote sensing and image interpretation is universally compatible with any devices to read.

1,802 citations

Journal ArticleDOI
TL;DR: EDM has been used for predicting the performance about placement of final year students by using the attributes such as academic records, age, and achievement etc., and based on the result, higher education organizations can offer superior education to its students.
Abstract: he purpose of higher education organizations have to offer superior education to its students. The proficiency to forecast student's achievement is valuable in affiliated ways associated with organization education system. Students' scores which they got in an exam can be used to invent training set to dominate learning algorithms. With the academia attributes of students such as internal marks, lab marks, age etc., it can be easily predict their performance. After getting predicted result the performance of the student to engage with desirable assistance to the students will be improved. Educational Data Mining (EDM) offers such information to educational organization from educational data. EDM provides various methods for prediction of students performance, which improve the future result of students. In this paper, by using the attributes such as academic records, age, and achievement etc., EDM has been used for predicting the performance about placement of final year students. Based on the result, higher education organizations can offer superior education to its students. KeywordsMining, Educational Data Mining, Sum of Difference, Prediction.

8 citations

Journal ArticleDOI
TL;DR: A combination of the RBP and RIFCM is used to propose an approach and apply it to leukemia images to establish the superiority of the approach in medical diagnosis in comparison to the conventional, as well as uncertainty based approaches.
Abstract: Several image segmentation techniques have been developed over the years to analyze the characteristics of images. Among these, the uncertainty based approaches and their hybrids have been found to be more efficient than the conventional and individual ones. Very recently, a hybrid clustering algorithm, called Rough Intuitionistic Fuzzy C-Means RIFCM was proposed by the authors and proved to be more efficient than the conventional and other algorithms applied in this direction, using various datasets. Besides, in order to remove noise from the images, a Refined Bit Plane RBP algorithm was introduced by us. In this paper we use a combination of the RBP and RIFCM to propose an approach and apply it to leukemia images. The aim of the paper is twofold. First, it establishes the superiority of our approach in medical diagnosis in comparison to most of the conventional, as well as uncertainty based approaches. The other objective is to provide a computer-aided diagnosis system that will assist the doctors in evaluating medical images in general, and also in easy and better assessment of the disease in leukaemia patients. We have applied several measures like DB-index, D-index, RMSE, PSNR, time estimation in depth computation and histogram analysis to support our conclusions.

4 citations

Dissertation
01 Jan 2018
TL;DR: The novel output of this work is development of bespoke calibration algorithms that remove radial/tangential distortion from the data captured using any MLA based camera, and, a light field camera independent algorithm that allows the delivery of 3D coordinate data in absolute units within a well-defined measurable range from a given camera.
Abstract: Digital cameras are increasingly used for measurement tasks within engineering scenarios, often being part of metrology platforms. Existing cameras are well equipped to provide 2D information about the fields of view (FOV) they observe, the objects within the FOV, and the accompanying environments. But for some applications these 2D results are not sufficient, specifically applications that require Z dimensional data (depth data) along with the X and Y dimensional data. New designs of camera systems have previously been developed by integrating multiple cameras to provide 3D data, ranging from 2 camera photogrammetry to multiple camera stereo systems. Many earlier attempts to record 3D data on 2D sensors have been completed, and likewise many research groups around the world are currently working on camera technology but from different perspectives; computer vision, algorithm development, metrology, etc. Plenoptic or Lightfield camera technology was defined as a technique over 100 years ago but has remained dormant as a potential metrology instrument. Lightfield cameras utilize an additional Micro Lens Array (MLA) in front of the imaging sensor, to create multiple viewpoints of the same scene and allow encoding of depth information. A small number of companies have explored the potential of lightfield cameras, but in the majority, these have been aimed at domestic consumer photography, only ever recording scenes as relative scale greyscale images. This research considers the potential for lightfield cameras to be used for world scene metrology applications, specifically to record absolute coordinate data. Specific interest has been paid to a range of low cost lightfield cameras to; understand the functional/behavioural characteristics of the optics, identify potential need for optical and/or algorithm development, define sensitivity, repeatability and accuracy characteristics and limiting thresholds of use, and allow quantified 3D absolute scale coordinate data to be extracted from the images. The novel output of this work is; an analysis of lightfield camera system sensitivity leading to the definition of Active Zones (linear data generation good data) and In-active Zones (non-linear data generation poor data), development of bespoke calibration algorithms that remove radial/tangential distortion from the data captured using any MLA based camera, and, a light field camera independent algorithm that allows the delivery of 3D coordinate data in absolute units within a well-defined measurable range from a given camera.

2 citations

Journal Article
TL;DR: Most affected phase of the leukemia cancer is possible by applying the parallel saliency algorithm over cancer images, and PSA works in a multi-core environment in comparison with the existingSaliency algorithm.
Abstract: Parallel Saliency algorithm is applied to solve the medical issues and to reduce the doctors' work in the society. Prediction of specific area of a leukemia, cancer image can be made using a Parallel Saliency algorithm (PSA). Firstly, most affected phase of the leukemia cancer is possible by applying the parallel saliency algorithm over cancer images, secondly, PSA works in a multi-core environment in comparison with the existing saliency algorithm. As a whole, the paper deals with PSA, which provides efficient performance to researchers and scientist.

1 citations