scholarly journals Eyeball Controlled Wheelchair

2020 ◽  
pp. 238-247
Keyword(s):  
Image Processing ◽  
The Elderly ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Indoor Space ◽  
Driver Circuit ◽  
The Individual ◽  
Driving Circuit ◽  
Eye Gesture

: A basic wheelchair is a gadget for people influenced by moderate, extreme physical incapacities and interminable disease. It is also meant for the elderly people. Many people with disabilities cannot manage the energized wheelchair operating joystick, sound, furthermore, hand developments as it is harder for the individual to do such specific tasks also it is programming focused. This strategy comprises of equipment which reduces the person's work utilizing the image processing method. This model comprised of a camera that tracks the eyeball movement and hence the position of the pupil by the image processing technique. And thereby the wheelchair is constrained by a user’s eye gesture in an indoor space. When the development has been initiated and it is given to the Raspberry pi for processing. The procedure relies on the feed coding and an output is given into the driver circuit. Likewise, the hindrance location sensors will be associated as an Emergency Brake that gives necessary conditions for the conventional activity of the wheelchair framework. Every one of the four wheels are associated with a driving circuit that moves the wheelchair

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

scholarly journals Design and Development of an Intelligent System for Pothole and Hump Identification on Roads

2019 ◽  
Vol 8 (3) ◽  
pp. 5294-5300 ◽  
Keyword(s):  
Image Processing ◽  
Fuel Consumption ◽  
Intelligent System ◽  
Processing Technique ◽  
Simple Solution ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Ultrasonic Sensors ◽  
Design And Development ◽  
Geographical Position

Country’s economy depend on well-maintained roads as they are major means of transportation. It becomes essential to identify pothole and humps in order to avoid accidents and damages to the vehicles that is caused because of distress to drivers and also to save fuel consumption. In this regard, this work presents a simple solution to detect potholes and humps and hence avoid accidents and help drivers. Potholes are detected using Image Processing Technique and Ultrasonic Sensors are used to detect humps. Controlling device used is Raspberry Pi. The system acquires the geographical position of potholes using Wi-Fi and transmits it to authorities to take corrective measures

A Novel Approach of Controlling Stoppage of Drip Infusion Using Image Processing on Raspberry PI Platform

2021 ◽  
Vol 58 (S) ◽  
pp. 65-72
Author(s):  
Hartono Pranjoto ◽  
Lanny Agustine ◽  
Diana Lestariningsih ◽  
Yesiana Dwi Wahyu Werdani ◽  
Widya Andyardja ◽  
...  
Keyword(s):  
Image Processing ◽  
Digital Camera ◽  
Detection Algorithm ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Novel Approach ◽  
Pinch Valve ◽  
Canny Edge ◽  
Infusion Fluid

Intravenous drip diffusion is a common practice to treat patients in hospitals. During treatment, nurses must check the condition of the infusion bag frequently before running out of fluid. This research proposes a novel method of checking the infusion bag using an image processing technique on a compact Raspberry PI platform. The infusion monitoring system proposed here is based solely on capturing the image of the infusion bag and the accompanying bag/ tube. When the infusion fluid enters the patient, the surface of the liquid will decrease, and at the end will reach the bottom of the infusion bag. When the image of the fluid surface touches the bottom of the infusion bag, a mechanism will trigger a relay, and then activate a pinch valve to stop the flow of the infusion fluid before it runs out. The entire system incorporates a digital camera and Raspberry as the image processor. The surface of the liquid is determined using the Canny Edge Detection algorithm, and its relative position in the tube is determined using the Hough Line Transform. The raw picture of the infusion bag and the processed image are then sent via a wireless network to become part of a larger system and can be monitored via a simple smartphone equipped with the proper application, thus becoming an Internet of Things (IoT). With this approach, nurses can carry on other tasks in caring for the patients while this system substitutes some work on checking the infusion fluid.

scholarly journals Human Distance Estimation using Quadcopter for Surveillance Purpose

2019 ◽  
Vol 8 (12S2) ◽  
pp. 483-488
Keyword(s):  
Image Processing ◽  
Everyday Life ◽  
Unmanned Aerial Vehicles ◽  
Crime Rate ◽  
Processing System ◽  
Distance Estimation ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Aerial Vehicles

Nowadays, quadcopters are commonly used. Quadcopters are unmanned aerial vehicles with four propellers to provide lift to fly and hover above ground. Quadcopter nowadays is a very common commercial item in everyday life. Some quadcopters are designed to do 3D or 2D mapping of a certain area or to take videos or just for entertainment purposes. Quadcopter is a very versatile item and is able to change into anything for example a quadcopter can also be used for security purposes to decrease the crime rate of our country. The objective of this study is to design and develop a quadcopter with image processing system to have the ability to measure the distance of a human from the drone itself. The quadcopter is designed to be small in size and have a mini computer like Raspberry Pi on top of it to compute the algorithm to calculate the distance of the human by using image processing technique through the camera which is setup on the drone. Human detecting algorithm YOLO and software Open CV is chosen to detect human and calculate the distance from the quadcopter. The results show that the system is quite limited by the capabilities of the hardware. The system shows an accuracy of more than 90 percent when the human is standing within a certain range. Both the accuracy of the distance sensing and human recognizing system is affected by the limitation of the hardware.

scholarly journals Smart Leaf Recognition System

2020 ◽  
Vol 9 (5) ◽  
pp. 289-291
Keyword(s):  
Image Processing ◽  
Early Stage ◽  
Recognition System ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Plant Leaves ◽  
Plant Leaf ◽  
Automatic Technique

One of major issue nowadays is the agricultural productivity which is something our Nation’s economy highly depends. Technology based advancements may lead to detection of diseases in plants which are quite natural. Care should be taken in this area before it causes serious effects on plants which mainly affect the product quality, quantity or productivity. Early stage detection of diseases in plants through some automatic technique is beneficial as it reduces a huge work of monitoring in large acres of crops. When they appear on plant leaves, earlier detection helps us to increase the yield and productivity. This paper presents an algorithm for image processing technique which is used for automatic detection and classification of plant leaf diseases with the help of raspberry pi and sensors. This survey is about different diseases and its classification, techniques which are used for plant leaf disease detection and also its respective fertilizer sprayed on the leaves.

scholarly journals Footprint-Based Health Monitoring Database using Raspberry PI

2020 ◽  
Vol 8 (6) ◽  
pp. 851-854
Keyword(s):  
Image Processing ◽  
Health Monitoring ◽  
Processing System ◽  
Processing Technique ◽  
Health Condition ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Data Allocation ◽  
Color Analysis ◽  
The Web

The health monitoring of the person can be done in the different ways. The health of the patient can be determined by the image processing technique. The biometric parameters can gather the details of the health condition of the patient. The digital image processing can be applied in the various filed such as medical, geology, research etc., In this paper they proposes the foot print technology this can capture the foot print of the patient by using the web cam. The captured image can be analyzed by using the shape and the dimension analysis. The foot print can reads the each person identity. Based upon the identity and the numbers the image processing system is implemented. It uses the raspberry pi as the main part. The data which is captured by the web cam can be stored in the SD card. The data allocation is done in the memory path. The classification of the data is takes place by using the data separation algorithm. The color analysis can takes place a significant place based upon the color we can able to classify the foot print and makes it for further analysis. There are several steps can be took place the image acquisition, edge detection, feature extraction, pattern recognition, pattern matching. The matched image can be provided as the better result. Based upon the result the health condition can be predicted. This method is highly effective and accurate when compared to other method

scholarly journals A Scientific Analysis to Observe Uniqueness in Lip Print Pattern

2021 ◽  
Vol 10 (4) ◽  
pp. 196-198
Author(s):  
N. B. Pushpa ◽  
N.B. Prajwala
Keyword(s):  
Image Processing ◽  
Face Recognition ◽  
Processing Technique ◽  
Individual Characteristics ◽  
Image Processing Technique ◽  
Forensic Investigation ◽  
Scientific Analysis ◽  
Investigation Technique ◽  
Palm Print ◽  
The Individual

Every individual have their unique identification like palm print, signature, finger print, face recognition, lip print etc.. here in this research one such effort is made to analyses lip print and identify the individual using their lip print. The wrinkle and grooves pattern on the lips has individual characteristics like tongue prints, face recognition, iris pattern, fingerprints. Cheiloscopy is a forensic investigation technique that deals with identification of humans based on lips traces. Image processing technique is used, lip print of the individual is captured, processed and analyzed for conclusion.

scholarly journals Monitoring System of Drowsiness and Lost Focused Driver Using Raspberry Pi

2020 ◽  
Author(s):  
Kusworo ADI ◽  
Catur Edi WIDODO ◽  
Aris Puji WIDODO ◽  
Hilda Nurul ARISTIA
Keyword(s):  
Image Processing ◽  
Processing Technique ◽  
High Accuracy ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Cascade Classifier ◽  
The Face ◽  
Haar Cascade ◽  
Two Parameters ◽  
Significant Factors

Background: Drowsiness condition is one of the significant factors often encountered when an accident occurs. We aimed to detect a method to prevent accidents caused by drowsiness and lost a focused driver. Methods: The image processing technique has been capable of detecting the characteristic of drowsiness and lost focus driver in real-time using Raspberry Pi. Video samples were processed using the Haar Cascade Classifier method to identify areas of the face, eyes, and mouth so that drowsy conditions. The methods can be determined based on the bject detected. Results: Two parameters were determined, the lost focused and drowsiness driver. The highest accuracy value for driver lost focused detection was 88.00%, while the highest accuracy value for drowsiness driver detection was 90.40%. Conclusion: In general, a system developed with image processing methods has been able to monitor the drowsiness and lost focused drivers with high accuracy. This system still needs improvements to increase performance.

A New Image Processing Technique for STEM

1974 ◽  
Vol 32 ◽  
pp. 432-433
Author(s):  
Yasushi Kokubo ◽  
Hirotami Koike ◽  
Teruo Someya
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Scanning Electron Microscopy ◽  
Elastic Scattering ◽  
Field Emission ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Energy Analyzer ◽  
Scanning Microscope ◽  
Scanning Electron

One of the advantages of scanning electron microscopy is the capability for processing the image contrast, i.e., the image processing technique. Crewe et al were the first to apply this technique to a field emission scanning microscope and show images of individual atoms. They obtained a contrast which depended exclusively on the atomic numbers of specimen elements (Zcontrast), by displaying the images treated with the intensity ratio of elastically scattered to inelastically scattered electrons. The elastic scattering electrons were extracted by a solid detector and inelastic scattering electrons by an energy analyzer. We noted, however, that there is a possibility of the same contrast being obtained only by using an annular-type solid detector consisting of multiple concentric detector elements.

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