Narula Institute of Technology

About: Narula Institute of Technology is a based out in . It is known for research contribution in the topics: Quantum dot cellular automaton & Cognitive radio. The organization has 288 authors who have published 490 publications receiving 2258 citations. The organization is also known as: NiT.

Face Detection and Extraction Using Viola–Jones Algorithm

Abstract: In the current times, face detection by computer system has become a major field of interest. Face detection technology can be applied to various fields-including security, biometrics, law enforcement, entertainment, and personal safety—to provide surveillance and tracking of people in real time. Face detection applications use algorithms to find only the human faces within larger images. Face detection algorithms typically start by searching for human eyes, one of the easiest features to detect. The algorithm might then attempt to detect eyebrows, mouth, nose, nostrils and the iris. Once the algorithm concludes that it has found a facial region, it applies additional tests to confirm that it has, in fact, detected a face. In this report, we propose a human face detection method for colored as well as gray images. Also, we cropped the particular detected facial image and extracting and showing the individual cropped image if the input image contains many faces.

Fuzzy Logic and Log-Sigmoid Function Based Vision Enhancement of Hazy Images

Abstract: This paper proposes a novel single image haze removal algorithm, which aims at generating artifact free, contrast enhanced haze free images. The proposed algorithm is designed to overcome the halo artifacts arising in output images obtained from various popular existing image haze removal methods and to restore the contrast of images which are degraded by scattering of scene light by aerosol particles present in the atmosphere. Here the halo artifacts are removed from output images by using a patch-independent procedure for dark channel evaluation and the contrast of images are restored by using a novel Type 1 fuzzy logic and log-sigmoid function based contrast enhancement procedure. Three fuzzy production rules are created considering pixel intensity values and log-sigmoid function values as input fuzzy linguistic variables and mapping constant as output fuzzy linguistic variable. The fuzzy logic is used here for automatic evaluation of membership function value of unique mapping constant for each pixel, which after defuzzification is used to map each pixel intensity value from the degraded image to corresponding pixel intensity value in the enhanced image. The efficiency of this proposed algorithm is established by obtaining satisfactory results from comparative studies of qualitative and quantitative analyses results which are carried out by applying the proposed algorithm and several other popular algorithms on same set of hazy images. Two significant quantitative parameters are chosen for performing quantitative analysis-a) Elapsed Time (time required for the execution of the algorithm) and Contrast-to-Noise Ratio which is an important visibility metric to measure visual quality of images. For both types of parameters it has been shown that our algorithm gives better results compared to other methods.

Design and Delay Analysis of Column Decoder Using NMOS Transistor at Nano Level for Semiconductor Memory Application

Abstract: Column decoder is the part of semiconductor memory used to retrieve the data from locations addressed by row decoder. In this paper 2–4 column decoder based on NMOS transistor has been designed with enhanced decoding speed at 150 nm channel length of transistor. The circuit is simulated using T-SPICE software. On voltage of the bit sources has been changed in accordance with the voltage of power supply V dd to report the variation of delay for decoding column.

Study on surface plasmon-based improvement in absorption in plasmonic solar cell

Abstract: Recently, plasmonics offers very high attention and greatly deals with various field includes the nanophotonics domain. In the plasmonic field, when the nanoparticle is much smaller than the wave length of light, coherent oscillation of the conduction band electrons induced by interaction with an electromagnetic field and conjointly improves absorption through scattering. In this paper, we studied the effectiveness of nanoparticle dimension to enhance extinction in terms of absorption and scattering for silver, gold, copper and aluminium nanoparticles. We also studied finite difference time domain-based solar cell model that improves various simulated plasmonic field components and observed that the high sensitivity of the surface plasmon resonance spectrum of noble metal nanoparticles to adsorbate induced changes in dimension and dielectric constant of the surrounding nanoenvironment. We also observed that noble metal specifically silver and gold nanoparticles significantly improve optical absorption than copper and aluminium nanoparticles.