Advances in Intelligent Informatics by El-Sayed M. El-Alfy, Sabu M. Thampi, Hideyuki Takagi, Selwyn

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

This booklet encompasses a collection of refereed and revised papers of clever Informatics tune initially provided on the 3rd overseas Symposium on clever Informatics (ISI-2014), September 24-27, 2014, Delhi, India. The papers chosen for this song hide a number of clever informatics and similar issues together with sign processing, trend popularity, picture processing info mining and their applications.

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S. Natteshan and J. : Statistical Feature measures computed from gray level co-occurrence matrices. : Run length encoding for volumetric texture. : Gray level manipulation experiments for texture analysis. net An Investigation of fSVD and Ridgelet Transform for Illumination and Expression Invariant Face Recognition Belavadi Bhaskar, K. P. Geetha Abstract. This paper presents a wide-eyed yet effective framework for face recognition based on the combination of flustered SVD(fSVD) and Ridgelet transform.

Mahapatra, and A. : Non-linear grayscale image enhancement based on firefly algorithm. C. ) SEMCCO 2011, Part II. LNCS, vol. 7077, pp. 174–181. : Performance evaluation of a fraud detection system based artificial immune system on the cloud. : Revisiting negative selection algorithms. : Image Similarity Search using a Negative Selection Algorithm. : Improved thresholding based on negative selection algorithm (NSA). : A comprehensive review of image enhancement techniques. : Gray-scale image enhancement as an automatic process driven by evolution.

There are 83 tumor affected and 9 non tumor grayscale images in DICOM format. 2 Performance Analysis of FCM on Original and Reduced Image Data The performance of FCM on original and reduced image data is analyzed by considering the time in seconds for the algorithm to complete. Every image in the dataset is segmented into four clusters using FCM. The time taken to perform the segmentation on original and reduced image data is measured. The average running time is calculated by repeating the segmentation process on every image for five times.

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