Keywords : Image processing


Weapon Detection System in Remotely Operated ASV

Muniyandy Elangovan; Yuvan Siddarth B.; Govindram Uduupa R; Vigneshwar R.

International Research Journal on Advanced Science Hub, 2021, Volume 3, Issue Special Issue 9S, Pages 34-37
DOI: 10.47392/irjash.2021.246

High tensions within states or across borders are quite common nowadays. Protection of human resources i.e., soldiers is as important as the protection of national resources. It is a visible fact that the causality rate among the defense forces during a crisis is relatively higher. That is the reason why a majority of Governmental organizations of various nations are stressing the concepts of Automation. ROV or Remotely Operated Vehicle, a concept of automation, is playing a very vital role in almost all the advancements in this technologically developed society. Present work, one complete Armored Safety Vehicle (ASV) was designed with more featured to accommodate sensors for detection and coding are developed o detect the weapon using the image processing techniques. There is a special wheel design is introduced which is safe for easy and quick movement of a vehicle. From commercial vehicles to exploring the deepest trenches, ROV’s have been a substantial tool for developmental prospects. It was tested for one image file and worked well. It is integrated with Machine Learning and image processing concepts to automatically come up with solutions based on the inputs. These concepts when used in defense vehicles not only increase efficiency but also reduces the casualty rate during a crisis.

Investigation into the Implementation of Medical Imaging

Bharath Bhaskar; Arjun Kundapur

International Research Journal on Advanced Science Hub, 2021, Volume 3, Issue Special Issue 9S, Pages 43-51
DOI: 10.47392/irjash.2021.248

In this article, we evaluate and discuss the implications of data analytics and Hadoop on clinical image analysis based on predictive algorithms. Each day, the healthcare industry analyses massive amounts of data. A large number of images were produced by various instruments on the patient in various medical situations. Numerous image processing methods and techniques are being developed in an attempt to obtain the most accurate information from images in order to provide an accurate diagnosis. To achieve maximum performance, both current and constantly evolving big data and hadoop ideas may provide more from image processing. The article examines the importance of big data analytics and hadoop in medical image processing utilizing HIPI and Map reduction inside the future implementation of Big data analytics (BDA) and Map reduction.

Driver Alert System Using Deep Learning and Machine Learning

Krithika G K; Karthik S; Kowsalya R; Alfred Daniel J; Sangeetha K

International Research Journal on Advanced Science Hub, 2021, Volume 3, Issue Special Issue ICARD-2021 3S, Pages 120-123
DOI: 10.47392/irjash.2021.078

The rising number of road injuries is one of the most pressing challenges facing the world today. One of the main causes of traffic accidents were unsafe and inattentive driving. Drowsiness or a loss of focus on the part of the driver is believed to be a significant factor in such incidents. Driver drowsiness tracking research can assist in the reduction of road accidents.This journal presents a good approach for applying a driver's sleepiness alarm system  that uses Machine Learning and Deep Learning techniques to identify and track the driver's yawning and sleepiness. For face detection and recognition, the device utilises the Histogram Centred Gradient (HOG) function descriptor, which is widely used in image processing. The SVM is then used to determine if the image being identified is a face or not. It also checks the driver's Eye Aspect Ratio (EAR) and Mouth Aspect Ratio (MAR) up to a certain countable frames to see whether he or she is sleepy or yawning. Since the driver's drowsiness or fatigue is proportional to the number of hours spent behind the wheel, an extra element for changing theface and mouth reference frames have been added. This increases the sensitivity to detect drowsiness. This also necessitates the introduction of face recognition so that each driver can be tracked individually.This Project aims to provide a Driver Alert System consisting of three sections Face Recognition to unlock vehicle, traffic light detection and Drowsiness alert system.

New Insights into Image Restoration Using Filter Analysis and Noise Models

Mettina Varghese; Yatin Yadav

International Research Journal on Advanced Science Hub, 2021, Volume 3, Issue Special Issue ICOST 2S, Pages 69-75
DOI: 10.47392/irjash.2021.042

Image restoration, by eliminating noise and blur from an image, restores the original image. In certain cases, image blur is inevitable, and to eliminate blur caused by camera shake or radar imaging or to remove the effect of image system reaction, etc. There are many suggested methods for noise removal and our paper will investigate and address various models of noise and blur and methods of restoration. There are numerous techniques developed, the most efficient being the Wiener filter and is the fundamental noise reduction approach. Wiener filters may cause some undesired effects in image restoration (significant degradation in quality). Various techniques and models are approached in the establishment of the power spectrum of noise and undegraded images. In terms of noise reduction and image restoration, this paper studies the Wiener filter's assumption and quantitative performance improvement. The SNR is improved considerably. But noise reduction is directly proportional to image degradation. To counter this, we must have prior knowledge of the original image by some PDF (Probability Distribution Function).