Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Multi-level image segmentation is a critical task in image processing that involves multiple threshold values. As the high computational cost of an exhaustive search is inefficient and cumbersome, the optimal thresholds algorithms make for a better path to venture; hence a comparison of optimization algorithms to set the optimal thresholds is highly essential and beneficial. In this paper, a practical comparison is made to deduce the best optimization technique amongst the whale optimization and antlion optimization algorithm, to solve the multilevel threshold problem, to find the optimal multilevel thresholds. Otsu's function is maximized to perform optimized thresholding-based image segmentation. The experimental results showed that the Antlion optimization algorithm gave better performance in solving the problem for higher level multi-thresholding.

VIT Unitversity

Department of Embedded Technology

School of Electronics Engineering

Vellore Campus

2019 Innovations in Power and Advanced Computing Technologies (i-PACT)

Antlion optimization and Whale optimization Algorithm for multilevel thresholding segmentation

World University root node

2019 International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN)

IBIS model generation and validation of CMOS Buffer

Specific Absorption Rate (SAR), ways to find in mobile devices, its measurement and side effects on human

In SoC, every module must function properly even after fabrication. If a module is behaving properly in terms of it's functionality during the designing of the chip, it must be ensured that the module should work properly after the chip is being fabricated. This is because due to some manufacturing defect, the module may not function properly. As the process of manufacturing requires fine precision, the chip must undergo testing during it's designing phase. This is called design for testing. In SoC, it's an utmost important to insert DFT ( Design For Testing ) components to all the IP and the modules present in the SoC. There are many modules in SoC which contains thousands of flops. It's scan version is scan flops. During design for testing, a sequence of data is being sent to the scan flops which are stitched to each other in serial manner. The data is captured, shifted from the previous flop to the next flop and the value is loaded. The final output sequence is obtained from the final flip flop and is observed for proper functionality. Propagating signal from one flop to another flop is not an easy task as the sequence needs to be propagated from flops to flops thus experiencing delay, glitch, etc. All the scan flops must receive signals from proper source to avoid coverage loss. Thus early testability of RTL is necessary which detects the fault if the flop is not receiving proper signal and if some signal dedicated for scan operation is not properly constrained. Generally, the scan coverage may vary from 20 % to 100 %. There are partition achieving 100 % coverage but there are some partition too having coverage of just 20 % and the aim is to increase the scan coverage thus minimising the coverage loss to ensure proper scan operation. © 2019 IEEE.

Proceedings - International Conference on Vision Towards Emerging Trends in Communication and Networking, ViTECoN 2019

Estimating Stuck at Coverage percentage through scan flops during scan

For the past decade, many researchers have been working towards the improvement in the visibility of single hazy images, using the haze image model. According to the haze image model, the hazy-free image is restored by estimating the atmospheric light and transmission from a hazy image. The objective of this proposed work is to improve the perceptibility by decreasing the density of haze in the hazy images. The research work was carried to estimate the optimal value of atmospheric light by tuning the weights using a bioinspired technique called Particle Swarm Optimization (PSO) based on the objective of minimizing the fog density. We have selected a fitness function or objective function which incorporates all statistical features to differentiate a clear image from the hazy image. The results are validated with the state-of-the-art, by measuring fog density of the restored image using Fog Aware Density Evaluator (FADE). Also, the results are validated by measuring the Peak signal to noise ratio (PSNR) and structural similarity index (SSI) using ground truth images from Foggy Road image database (FRIDA). This research work demonstrates better results qualitatively and quantitatively. © 2019, Science and Information Organization.

Department of Communication Engineering

Fulltext

International Journal of Advanced Computer Science and Applications

Atmospheric Light Estimation using Particle Swarm Optimization for Dehazing

Dehazing from a single image is still a challenging task, where the thickness of the haze depends on depth information. Researchers focus on this area by eliminating haze from the single image by using restoration techniques based on haze image model. Using haze image model, the haze is eliminated by estimating atmospheric light, transmission, and depth. A few researchers have focused on enhancement based methods for eliminating haze from images. Enhancement based dehazing algorithms will lead to saturation of pixels in the enhanced image. This is due to assigning fixed values to the parameters used to enhance an image. Therefore, the enhancement based methods fail in the proper tuning of the parameters. This can be overcome by optimizing the parameters that are used to enhance the images. This paper describes the research work carried to derive two enhanced images from a single input hazy image using particle swarm optimization and fuzzy intensification operators. The two derived images are further fused using multi-scale fusion technique. The objective evaluation shows that the entropy of the haze eliminated images is comparatively better than the state-of-the-art algorithms. Also, the fog density is measured using an evaluator known as fog aware density evaluator (FADE), which considers all the statistical parameters to differentiate a hazy image from a highly visible natural image. Using this evaluator we found that the density of the fog is less in our proposed method when compared with enhancement based algorithms used to eliminate haze from images. © 2019, Insight Society.

International Journal on Advanced Science, Engineering and Information Technology

Multi-scale fusion of enhanced hazy images using particle swarm optimization and fuzzy intensification operators

2018 3rd International Conference for Convergence in Technology (I2CT)

Development of Automation Test Suites for Validating GNSS Software

Humanity, moving to an era focused upon development has forgotten the importance of sustainability and has been the major culprit behind the rising pollution levels in the earth's atmosphere among all other living organisms. The pollution levels at some places have reached to such high extents that they have started harming our own health. Hence, it is a significant indication to keep track of pollution levels in our surroundings in order to ensure that we do not get affected by the ill effects of pollution and at the same time improvise our actions in order to maintain pollution free environmental conditions. So, this paper covers the design and development of a device prototype that monitors air and noise pollution in real time and sends alerts to desired authorities whenever the pollution levels cross the threshold via push notification service on mobile phones using a cloud service provider, hence setting an example for an efficient IOT (Internet of Things) device. © 2006-2018 Asian Research Publishing Network (ARPN).

ARPN Journal of Engineering and Applied Sciences

Pollution monitoring system using IOT

Maintenance of the solid waste is one of the biggest challenges faced by the municipal department today. Overflowing of dustbins not only pollute the environment but also have serious impact on our health. From inventing wheels to space shuttle, from discovering fire to life on mars our story is indeed a success story. But on the way to this jaw-dropping success humans became reckless and generated a lot of waste and management of these wastes is a serious concern for us. Municipal department, on the behalf of people, has taken several measures to address this concern. In our project we have taken one further step towards the management of these wastes generated in our day to day life. In this project our objective is to detect garbage level and foul smell coming from dustbins in a remote access and immediately transmit the information to municipal through Internet of Things (IoT). In addition to this, an alert message will be sent to driver of garbage collecting truck and an immediate action can be made to clean the dustbins. © 2018, Institute of Advanced Scientific Research, Inc. All rights reserved.

Journal of Advanced Research in Dynamical and Control Systems

Real-time garbage monitoring system with periodic updation of database server and notification using IOT and GSM

Outdoor Images captured under inclement weather conditions are degraded by various atmospheric particles, which vary in size and concentration. To restore the visibility of the degraded images, various state-of-the-art algorithms were developed for the past decade. In this paper, an overview of various research works carried over the past decade related to static weather conditions like Haze, fog and dynamic weather conditions like rain are investigated. Also, the merits and demerits of each algorithm along with the challenges in this area are focused. © 2006-2016 Asian Research Publishing Network (ARPN).

A review on visibilityrestoration of degraded images under inclementweather conditions

Objectives: Images captured under foggy or hazy conditions have low contrast and meager color. The proposed work is carried to improve the visibility of hazy images. Methods: The proposed method is based on 'dark channel prior' to remove haze, along with guided filter to refine the image due to the occurrence of halos. Even after refinement, halos are not completely removed. So, for further refinement edge preserving smoothing global filter L0 gradient minimization filter is used. Findings: This method has an advantage over conventional method by suppressing halos completely. Application/Improvements: The proposed method improves the contrast and increase in entropy reveals that the detail information is preserved effectively.

Indian Journal of Science and Technology

De-Hazing using Guided and L0 Gradient Minimization Filters

In this paper, we have developed a prototype mobile assistive device, which is able to solve the problem that visually impaired people faces every day. This device functions as assistive device for the visually impaired to navigate from one place to another especially while using public transport. In order to get transportation independently, the visually impaired use auditory touched clues like walking stick or white cane. The limitation of this device is that a visually impaired person must come into close proximity with their surroundings to determine the location of an obstacle. However, these devices can only assist the visually impaired at a pedestrian crossing. Therefore, we have developed an assistive device with an objective, for the visually impaired people to identify the vehicle, while using public transport. © Research India Publications.

International Journal of Applied Engineering Research

Assistive device for visually impaired

The fog and haze present in the atmosphere causes the degradation of the colour and contrast in the outdoor images and also affects the efficiency of image processing algorithms. Hence, a proper visibility restoration algorithm is required which can remove the fog and also preserve the scene. The visibility restoration algorithms are classified as enhancement based and restoration based. Nowadays the later based methods are used with a single image input. All the earlier algorithms have the problem of removing fog near depth discontinuity. Hence, an edge preserving filter is incorporated into the Tarel’s model which has better restoration capabilities.This method is ideal for real time applications like driver assistance, lane marking etc. Quantitative and qualitative evaluation from the results proves that it gives good results. © Research India Publications.