By Rituparna Chaki, Khalid Saeed, Sankhayan Choudhury, Nabendu Chaki
This e-book comprises the prolonged model of the works which have been awarded and mentioned within the First foreign Doctoral Symposium on utilized Computation and safeguard platforms (ACSS 2014) held in the course of April 18-20, 2014 in Kolkata, India. The symposium has been together geared up by means of the AGH college of technology & expertise, Cracow, Poland and college of Calcutta, India. the amount I of this double-volume ebook comprises fourteen prime quality e-book chapters in 3 assorted elements. half 1 is on trend attractiveness and it offers 4 chapters. half 2 is on Imaging and Healthcare purposes includes 4 extra booklet chapters. The half three of this quantity is on instant Sensor Networking and it contains as many as six chapters. quantity II of the publication has 3 components proposing a complete of 11 chapters in it. half four includes 5 very good chapters on software program Engineering starting from cloud provider layout to transactional reminiscence. half five in quantity II is on Cryptography with booklet chapters in it. half 6 of this quantity is on computing device Aided layout with 4 chapters in it. We strongly think that the twenty 5 chapters in those volumes of utilized Computation and safety structures might be favored through all its readers.
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Extra resources for Applied Computation and Security Systems: Volume One
Intell. 15(11), 1148–1161 (1993) 3. : The importance of being random: statistical principles of iris recognition. Pattern Recognit. 36(2), 279–291 (2003) 4. : Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. J. Opt. Soc. Am. A Opt. Image Sci. 2(7), 1160–1169 (1985) 5. : Biometric personal identification system based on iris analysis. US Patent Number 5, 291, 560, 1 Mar 1994 6. : Iris recognition: an emerging biometric technology.
After extraction of some points, total image is divided into several blocks of size 16 9 16 and find the number of points in each block and store them in a row vector. Hence, one row corresponds to one image and column corresponds to feature. So total number of features of a particular face or a row is (256 9 256)/ (16 9 16) = 256. But the 256 extracted features contain some noisy and irrelevant features. As a result, the performance of the system degrades. So selection of features which are relevant, free from noise, and redundancy is essential to improve the performance of the thermal face recognition system.
There are other kinds of population-based search algorithms in the literature, which is less expensive in times. Such algorithms are Genetic Algorithm (GA)-based method [18, 19, 20], and ant colony optimization (ACO)-based techniques have attracted a lot of attention  to the researchers. In this paper, we propose an efficient scheme for scale and rotation invariant thermal face recognition using scale invariant feature transform (SIFT). The main contributions of this work are as follows: • A complete scale and rotation invariant thermal face recognition system based on SIFT features are implemented.