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By Sabu M. Thampi, El-Sayed M. El-Alfy, Hideyuki Takagi, Selwyn Piramuthu, Thomas Hanne

ISBN-10: 331911218X

ISBN-13: 9783319112183

This e-book features a choice of refereed and revised papers of clever Informatics song initially awarded on the 3rd foreign Symposium on clever Informatics (ISI-2014), September 24-27, 2014, Delhi, India. The papers chosen for this song hide numerous clever informatics and similar themes together with sign processing, development reputation, snapshot processing, facts mining and their purposes.

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Extra resources for Advances in Intelligent Informatics (Advances in Intelligent Systems and Computing, Volume 320)

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Active contour method with locally computed signed pressure force function: An application to brain MR image segmentation. In: Seventh International Conference on Image and Graphics, pp. : Texture characterization based on GLCM. : Modified FCM approach for Brain MR Image segmentation. In: International Conference on Circuits, Power and Computing Technologies, pp. : Brain Tumor classification using Discrete Cosine transform and Probabilistic neural network. In: International Conference on Signal Processing Image Processing & Pattern Recognition (ICSIPR), pp.

Conclusion and future work are delineated at the end. 2 Proposed Methodology In this section, we key out the proposed face image depiction and classification technique. We take into account the primal issues of face recognition and reduce the effect of these in improving the accuracy of recognition. The proposed algorithm derives a new face image by using flustered SVD, which reduces the illumination problem. The features are extracted out of this image by applying ridgelet transform, which are invariant to lighting, facial expressions (open / closed eyes, smiling / not smiling) and facial details (glasses / no glasses)[22].

S. Natteshan and J. Angel Arul Jothi Abstract. Computer Aided Diagnosis (CAD) is a technique where diagnosis is performed in an automatic way. This work has developed a CAD system for automatically classifying the given brain Magnetic Resonance Imaging (MRI) image into ‘tumor affected’ or ‘tumor not affected’. The input image is preprocessed using wiener filter and Contrast Limited Adaptive Histogram Equalization (CLAHE). The image is then quantized and aggregated to get a reduced image data. The reduced image is then segmented into four regions such as gray matter, white matter, cerebrospinal fluid and high intensity tumor cluster using Fuzzy C Means (FCM) algorithm.

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Advances in Intelligent Informatics (Advances in Intelligent Systems and Computing, Volume 320) by Sabu M. Thampi, El-Sayed M. El-Alfy, Hideyuki Takagi, Selwyn Piramuthu, Thomas Hanne


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