International Journals

Permanent URI for this collectionhttps://dspace.psgrkcw.com/handle/123456789/157

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    A SURVEY ON DETECTING BRAIN TUMOR IN MRI IMAGES USING IMAGE PROCESSING TECHNIQUES
    (International Journal of Innovative Research in Computer and Communication Engineering, 2015-01) A, Sindhu; S, Meera
    Medical Image Processing is the fast growing and challenging field now a days. Medical Image techniques are used for Medical diagnosis. Brain tumor is a serious life threatening disease. Detecting Brain tumor using Image Processing techniques involves four stages namely Image Pre-Processing, Image segmentation, Feature Extraction, and Classification. Image processing and neural network techniques are used to improve the performance of detecting and classifying brain tumor in MRI images. In this survey various Image processing techniques are reviewed particularly for Brain tumor detection in magnetic resonance imaging. More than twenty five research papers of image processing techniques are clearly reviewed.
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    A STUDY OF TECHNIQUES ON SECURING PATIENT CONFIDENTIAL INFORMATION USING ECG STEGANOGRAPHY
    (International Journal of Engineering Research and Applications, 2018-10) Radha N; Rehana Banu H
    Plants play an important role in the earth’s ecology. Without plants, human lives cannot exist in this world. But in the recent days, people are not having knowledge about many types of valuable plants. They are at the risk of extinction. So, it is necessary to protect plants and to catalogue various types of flora diversities and it is important to maintain plant databases which pave a way towards conservation of earth’s biosphere. In the world wide, there are a huge number of plant species available. To handle such volumes of information, development of a quick and efficient classification tool using machine learning algorithms is needed. In addition to the conservation aspect, recognition of plants paves a way to use those plants as an alternative energy source. In this paper, various techniques used to classify the leaf images using machine learning algorithms are studied.