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 publication encompasses a choice of refereed and revised papers of clever Informatics tune initially offered 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 themes together with sign processing, trend acceptance, photo processing info mining and their applications.

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This algorithm granted the best result in disease detection in L*a*b* color space. On the other side, Grundland and Dodgson [7] introduced a new contrast enhanced color to grayscale conversion algorithm for real-scenes in real-time. They used image sampling and dimension reduction for the conversion. They transformed a colored image to a high contrast grayscale for better understanding. But again losing information in this dimension reduction which creates problem of under segmentation. e. grayscale images) [9].

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. Table 5 shows the comparison of average running time for FCM for Automatic Classification of Brain MRI Images Using SVM 27 original and reduced image data for seven sample images.

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. : A genetic algorithm approach to color image enhancement. : A Novel Fault Diagnostics and Prediction Scheme Using a Nonlinear Observer With Artificial Immune System as an Online Approximator.

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