Real-time Vision-Based Lane Detection with 1D Haar Wavelet Transform on Raspberry Pi

Rapid progress is being made towards the realization of autonomous cars. Since the technology is in its early stages, human intervention is still necessary in order to ensure hazard-free operation of autonomous driving systems. Substantial research efforts are underway to enhance driver and passenger safety in autonomous cars. Toward that end GreedyHaarSpiker, a real-time vision-based lane detection algorithm is proposed for road lane detection in different weather conditions. The algorithm has been implemented in Python 2.7 with OpenCV 3.0 and tested on a Raspberry Pi 3 Model B ARMv8 1GB RAM coupled to a Raspberry Pi camera board v2. To test the algorithm’s performance, the Raspberry Pi and the camera board were mounted inside a Jeep Wrangler. The algorithm performed better in sunny weather with no snow on the road. The algorithm’s performance deteriorated at night time or when the road surface was covered with snow

Hardware Implementation of a Novel Image Compression Algorithm

Image-related communications are forming an increasingly large part of modern communications, bringing the need for efficient and effective compression. Image compression is important for effective storage and transmission of images. Many techniques have been developed in the past, including transform coding, vector quantization and neural networks. In this thesis, a novel adaptive compression technique is introduced based on adaptive rather than fixed transforms for image compression. The proposed technique is similar to Neural Network (NN)-based image compression and its superiority over other techniques is presented It is shown that the proposed algorithm results in higher image quality for a given compression ratio than existing Neural Network algorithms and that the training of this algorithm is significantly faster than the NN based algorithms. This is also compared to the JPEG in terms of Peak Signal to Noise Ratio (PSNR) for a given compression ratio and computational complexity. Advantages of this idea over JPEG are also presented in this thesis

Android Attack Protection Application

Developed an android attack protection application. It is designed for people who are under attack. They would press a button on their phone and it will gather their current location and start recording a 5 second video with audio. This application will then automatically send the location and video straight to the person selected

IDENTIFICATION OF POTENTIAL INHIBITORS FOR LOWERING CHOLESTEROL LEVEL BY INHIBITING PCSK9

ABSTRACTObjective: PCSK9 has medical significance in lowering cholesterol levels. Inhibitors target and inactivate PCSK9 in the liver. Knocking out PCSK9 (proprotein convertase subtilisin kexin 9) reduces the amount of harmful LDL cholesterol circulating in the bloodstream. There are two known inhibitors for treating the cardiovascular disease Arilocumab†and Evalocumabâ€. However there are many side-effects. The current study is to identify natural and synthetic inhibitor using the pharmacophoric feature of the known inhibitor and validating the short listed candidates using Molecular dynamics and ADMET properties.Methods: Known inhibitors for the PCSK9 Protein were taken from the BINDING DATABASE. Molecular docking was performed for the known inhibitors with the PCSK9 protein. After docking the best inhibitor was selected and the docking result was then imported to find the pharmacophoric features.Results: The pharmacophore model was generated with 3 features containing  1 hydrogen bond acceptor(A),1 Hydrogen bond donor(B) and 1 Aromatic ring. The constructed e-pharmacophore model was screened with more than 20000 natural compounds. 5 compounds were short listed. Among them ZINC85625485 has  glide  score  of  -13.03  kcal/mol  with  glide  energy  was  -57.62 kcal/mol and ZINC85625406 has glide score of -8.1kcal/mol with glide energy was -39.33kcal/mol were taken as the best Hits.Conclusion: PCSK9 is known to be a therapeutic agent as it controls the plasma LDL cholesterol levels by posttranslational regulation of the LDL receptor. Therefore, up-regulation of PCSk9 can lead to elevated cholesterol level in such case inhibition of PCSK9 will be a effective remedy. In this study already known inhibitors were taken and pharmacophore feature was generated. Zinc database was screened to find out novel compounds with similar pharmacophore features that can act as potentially active compound against PCSK9. ZINC85625485 and ZINC85625406 were short listed as lead compounds with Molecular dynamics simulation and checking the ADMET properties. Keywords: PCSK9, Docking, ADMET, Molecular Dynamics.                                                            Â

Improved foreground detection via block-based classifier cascade with probabilistic decision integration

Background subtraction is a fundamental low-level processing task in numerous computer vision applications. The vast majority of algorithms process images on a pixel-by-pixel basis, where an independent decision is made for each pixel. A general limitation of such processing is that rich contextual information is not taken into account. We propose a block-based method capable of dealing with noise, illumination variations, and dynamic backgrounds, while still obtaining smooth contours of foreground objects. Specifically, image sequences are analyzed on an overlapping block-by-block basis. A low-dimensional texture descriptor obtained from each block is passed through an adaptive classifier cascade, where each stage handles a distinct problem. A probabilistic foreground mask generation approach then exploits block overlaps to integrate interim block-level decisions into final pixel-level foreground segmentation. Unlike many pixel-based methods, ad-hoc postprocessing of foreground masks is not required. Experiments on the difficult Wallflower and I2R datasets show that the proposed approach obtains on average better results (both qualitatively and quantitatively) than several prominent methods. We furthermore propose the use of tracking performance as an unbiased approach for assessing the practical usefulness of foreground segmentation methods, and show that the proposed approach leads to considerable improvements in tracking accuracy on the CAVIAR dataset

Development of solution processed, flexible, CuInSe₂ nanocrystal solar cells

Clean sources of energy, especially photovoltaics (PVs), are urgently needed to cope with global energy shortage and environmental pollution. For PVs to play a significant role in energy production, the current prices must be brought down. Thin film PVs made using layered Mo or Au/CuInGaSe₂(CIGS)/CdS/ZnO/ITO have already shown high efficiencies. Traditionally, most layers in CIGS solar cells are deposited using high-cost techniques requiring high temperatures and ultra-low pressures. By replacing the traditionally processed CIGS with a nanocrystal layer that can be deposited at mild processing conditions, the fabrication cost can be reduced. In this study, a high yielding synthesis method for CuInSe₂ nanocrystals has been developed which gives the best efficiency (3.1%), so far, for low-temperature processed CuInSe₂ nanocrystal PVs. An important challenge that nanocrystal solar cells currently face is low device efficiency, resulting in higher operating cost. CuInSe₂ nanocrystals can remain suspended in solution because of the long chain organic ligands attached to the surface. However, these ligands hinder charge transfer between nanocrystals causing low device efficiency. These ligands have been successfully replaced with smaller sulfide ions thereby improving the best efficiency of low-temperature processed CuInSe₂ nanocrystal solar cells from 3.1 % to 3.5%. Another approach to reducing the cost of CuInSe₂ PVs is by replacing the glass support medium with cheaper alternatives like paper. Flexible CuInSe₂ nanocrystal solar cells are successfully fabricated on paper with efficiencies reaching up to 2.25%. This is the first time a nanocrystal solar cell has been fabricated on paper. There is no significant loss in PV device performance after more than 100 flexes to 5 mm radius, and the devices continue to perform when folded into a crease. Apart from the absorber layer, the replacement of other high-temperature and vacuum processed device layers with ambient solution-processed layers lowers the manufacturing cost. This has been achieved by spin coating suitable nanomaterials as device layers. Lastly, for commercialization of CuInSe₂ nanocrystal solar cells, multiple devices need to be connected to achieve the desired current and voltage. A fabrication process has been developed for building multiple nanocrystal PVs on a single substrate using 3D printed masksChemical Engineerin

SUNSCREENS: DEVELOPMENTS AND CHALLENGES

One of the major concerns affecting the human skin is the exposure to ultra-violet radiations (UVR) causing photo-damage and skin cancers. In order to provide preventive measures against such incidences, there is an increased demand for sun-protectants. Sun screening agents have shown beneficiary effects on the skin by reducing the exposure of UVR and its associated symptoms. Although various constituents have been recognized to have sun protecting activity, their safety and efficacy is still a concern. The United States Food and Drugs Administration (USFDA) and European Guidelines (EU) guidelines have made the sun protecting factor (SPF) and other such indices compulsory on the labels of such formulas to guide the consumers for better selection. The various ranges of radiations and skin types influence the mechanism of photoreaction and subsequent choice of the formulation. Apart from existing agents, certain novel sun-screening agents and technologies are now available to provide better protection to human populations

MRF-based background initialisation for improved foreground detection in cluttered surveillance videos

Robust foreground object segmentation via background modelling is a difficult problem in cluttered environments, where obtaining a clear view of the background to model is almost impossible. In this paper, we propose a method capable of robustly estimating the background and detecting regions of interest in such environments. In particular, we propose to extend the background initialisation component of a recent patch-based foreground detection algorithm with an elaborate technique based on Markov Random Fields, where the optimal labelling solution is computed using iterated conditional modes. Rather than relying purely on local temporal statistics, the proposed technique takes into account the spatial continuity of the entire background. Experiments with several tracking algorithms on the CAVIAR dataset indicate that the proposed method leads to considerable improvements in object tracking accuracy, when compared to methods based on Gaussian mixture models and feature histograms