scholarly journals Real-time Liquid Level and color Detection system using Image Processing

2018 ◽  
Vol 7 (4) ◽  
pp. 223
Author(s):  
Fars E. Samann
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Chemical Reaction ◽  
Detection System ◽  
Chemical Study ◽  
Liquid Level ◽  
Average Accuracy ◽  
Color Detection ◽  
Liquid Level Detection

Detecting the level of the liquid is very essential for any chemical study in research labs. The objective of this paper is to design real-time liquid level detection system using image processing. Besides, this system is able to indicate the color of the liquid during chemical reaction. The proposed system was developed using vision assistant tools in LabVIEW and webcam. Regarding to webcam resolution, the average accuracy of the system is approximately 99%.

The Hardware Design and Implementation of Liquid Level Detection System for Lead-Acid Battery

2013 ◽  
Vol 860-863 ◽  
pp. 2850-2854 ◽  
Author(s):  
Ya Jun Bi ◽  
Hong Fei Li
Keyword(s):  
Detection System ◽  
Low Cost ◽  
Liquid Level ◽  
Lead Acid Battery ◽  
Infrared Transmission ◽  
Wireless Data ◽  
Linear Ccd ◽  
Infrared Technology ◽  
Liquid Level Detection ◽  
Lead Acid

The hardware structure of a liquid level detection system for lead-acid battery was briefly introduced. The system adopts AT89C51 MCU as host module, combined with display storage, extended storage and the watch dog technology. The slave module adopts AT89C2051 MCU, which driver the linear CCD to realize non-contact measurement in acidic and corrosive conditions. The infrared transmission module uses RS-232 serial-to-infrared technology to realize wireless data delivery. The damage due to sensor corrosion could be avoided in this system. Compared with other similar equipments, this system has the advantages of simple structure, small volume, low cost, high measure precision and convenient maintenance.

scholarly journals PENDETEKSIAN OBJEK ROKOK PADA VIDEO BERBASIS PENGOLAHAN CITRA DENGAN MENGGUNAKAN METODE HAAR CASCADE CLASSIFIER

2018 ◽  
Vol 1 (3) ◽  
pp. 92
Author(s):  
Kadek Oki Sanjaya ◽  
Gede Indrawan ◽  
Kadek Yota Ernanda Aryanto
Keyword(s):  
Image Processing ◽  
Detection System ◽  
High Accuracy ◽  
Special Study ◽  
Cascade Classifier ◽  
Integral Image ◽  
Main Method ◽  
Average Accuracy ◽  
Haar Features ◽  
Haar Cascade

Object detection is a topic widely studied by the scientists as a special study in image processing. Although applications of this topic have been implemented, but basically this technology is not yet mature, futher research is needed to developed to obtain the desired result. The aim of the present study is to detect cigarette objects on video by using the Viola Jones method (Haar Cascade Classifier). This method known to have speed and high accuracy because of combining some concept (Haar features, integral image, Adaboost, and Cascade Classifier) to be a main method to detect objects. In this research, detection testing of cigarettes object is in samples of video with the resolution 160x120 pixels, 320x240 pixels, 640x480 pixels under condition of on 1 cigarette object and condition 2 cigarettes object. The result of this research indicated that percentage of average accuracy highest 93.3% at condition 1 cigarette object and 86,7% in the condition 2 cigarette object that was detected on the video with resolution 640x480 pixels, while the percentage of accuracy lowest 90% at condition 1cigarette object, and 81,7% at the condition 2 cigarette objects, detected on the video with the lowest resolution 160x120 pixels. The percentage of average errors at detection cigarettes object was inversely with percentage of accuracy. So that the detection system is able to better recognize the object of the cigarette, then the number of samples in the database needs to be improved and able to represent various types of cigarettes under various conditions and can be added new parameters related to cigarette object

scholarly journals A Real Time Image Processing Bird Repellent System Using Raspberry Pi

2020 ◽  
Vol 5 (2) ◽  
Author(s):  
Oluwole Arowolo ◽  
Adefemi A Adekunle ◽  
Joshua A Ade-Omowaye
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Moving Objects ◽  
Detection System ◽  
Local Binary Patterns ◽  
Raspberry Pi ◽  
Feature Identification ◽  
Data Set ◽  
Haar Features ◽  
Haar Feature

Rice is one of the most consumed foods in Nigeria, therefore it’s production should be on the high as to meet the demand for it. Unfortunately, the quantity of rice produced is being affected by pests such as birds on fields and sometimes in storage. Due to the activities of birds, an effective repellent system is required on rice fields. The proposed effective repellent system is made up of hardware components which are the raspberry pi for image processing, the servo motors for rotation of camera for better field of view controlled by Arduino connected to the raspberry pi, a speaker for generating predator sounds to scare birds away and software component consisting of python and Open Cv library for bird feature identification. The model was trained separately using haar features, HOG (Histogram of Oriented Gradients) and LBP (Local Binary Patterns).Haar features resulted in the highest accuracy of 76% while HOG and LBP were, 27% and 72% respectively. Haar trained model was tested with two recorded real time videos with birds, the false positives were fairly low, about 41%. This haar feature trained model can distinguish between birds and other moving objects unlike a motion detection system which detects all moving objects. This proposed system can be improved to have a higher accuracy with a larger data set of positive and negative images. Keywords—Electronic pest repeller Haar cascade classifier, ultrasonic

scholarly journals Early warning flood detector adopting camera by Sobel Canny edge detection algorithm method

2021 ◽  
Vol 22 (3) ◽  
pp. 1796
Author(s):  
Satryo B. Utomo ◽  
Januar Fery Irawan ◽  
Rizqi Renafasih Alinra
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Water Level ◽  
Real Time ◽  
Early Warning ◽  
Detection System ◽  
Water Levels ◽  
Level Gauge ◽  
Canny Edge Detection ◽  
Canny Edge

Early warning of floods is an essential part of disaster management. Various automatic detectors have been developed in flood mitigation, including cameras. But reliability and accuracy have not been improved. Besides, the use of monitoring devices has been employed to monitor water levels in various water building facilities. The early warning flood detector was carried out with a sensor camera using an orange ball that floats near the water level gauge in a bounding box. This approach uses the integration of computer vision and image processing, namely digital image processing techniques, with Sobel Canny edge detection (SCED) algorithms to detect quickly and accurately water levels in real-time. After the water level is measured, a flood detection process is carried out based on the specified water level. According to the results of experiments in the laboratory, it has been shown that the proposed approach can detect objects accurately and fast in real-time. Besides, from the water level detection experiment, good results were obtained. Therefore, the object detection system and water level can be used as an efficient and accurate early detection system for flood disasters.

Defects Detection of Printed Circuit Board Based on the Machine Vision Method

2014 ◽  
Vol 494-495 ◽  
pp. 785-788 ◽  
Author(s):  
Wen Bin Wang ◽  
Dao Yuan Liu ◽  
Yu Qin Yao
Keyword(s):  
Image Processing ◽  
Image Registration ◽  
Real Time ◽  
Printed Circuit Board ◽  
Detection Efficiency ◽  
Detection System ◽  
Circuit Board ◽  
Algorithm Analysis ◽  
Real Time Processing ◽  
Morphological Image Processing

The processing of target image using image processing technology, can realize the non-contact online detecting circuit board, thus greatly improve the detection efficiency, reducing the defective rate. This paper provides the detection system based on the methods of pre-processing the standard circuit board image and the circuit board image to be detected, two value segmentation, morphological image processing, image registration and poor shadow detection processing, among them ,image registration is the key. In order to improve the processing speed to achieve real-time processing, image registration using rapid processing algorithm. Analysis of the experimental results, the method can detect the defects on the circuit board to be detected accurately, and can achieve the automatic real-time detection purposes.

The Design of Liquid Level Detection System for Oil Tank

2011 ◽  
Vol 130-134 ◽  
pp. 2443-2446
Author(s):  
Ai Ping Wu ◽  
He Ping Pan ◽  
Yong Hua Li
Keyword(s):  
Detection System ◽  
Capacitive Sensor ◽  
Logic Circuit ◽  
Liquid Level ◽  
Level Measurement ◽  
Liquid Level Measurement ◽  
Oil Tank ◽  
Processing Circuit ◽  
Easy Operation ◽  
Liquid Level Detection

The basic principle of liquid level measurement with capacitive sensor is described. According to differences in dielectric constant between oil and water, a liquid level detection system for oil tank is designed. The system includes capacitive sensor, signal processing circuit, FPGA logic circuit and the software of computer. Results show that the system has characteristics of easy operation, high precision. It can detect the change of liquid level accurately and effectively.

scholarly journals Micro pin header defect detection system based on OpenCV

2021 ◽  
Vol 2137 (1) ◽  
pp. 012037
Author(s):  
Houcheng Yang ◽  
Yinxin Yan ◽  
Zhangsi Yu ◽  
Zhang Ning
Keyword(s):  
Image Processing ◽  
Success Rate ◽  
Real Time ◽  
Light Source ◽  
Defect Detection ◽  
Detection Efficiency ◽  
Detection System ◽  
Experimental Tests ◽  
Quality Inspection ◽  
Detection Error

Abstract In order to solve the problems of low detection efficiency and large detection error in the process of manual quality inspection, a full-automatic defect detection system is built. The system uses an industrial camera, selects a suitable light source for image acquisition, uses the open source OpenCV visual library for image processing and defect contour recognition, and sets the screening conditions for unqualified products. The system can detect whether the needle arrangement has defects in real time and classify them according to different defect categories, It can greatly improve the detection efficiency of needle arranging production enterprises. Through a large number of experimental tests, the detection success rate can reach 98.67%, which shows that the system is feasible.

scholarly journals Severity Prediction System for Real Time Pothole Detection

2021 ◽  
Vol 23 (07) ◽  
pp. 1328-1334
Author(s):  
Sumit Bhimte ◽  
◽  
Hrishikesh hasabnis ◽  
Rohit Shirsath ◽  
Saurabh Sonar ◽  
...  
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Detection System ◽  
Detection Algorithm ◽  
Prediction System ◽  
Image Processing Algorithm ◽  
Efficient Technology ◽  
Severity Prediction ◽  
Pothole Detection ◽  
Real Time Application

Pothole Detection System using Image Processing or using Accelerometer is not a new normal. But there is no real time application which utilizes both techniques to provide us with efficient solution. We present a system which can be useful for the drivers to determine the intensity of Pothole using both Image Processing Technology and Accelerometer device-based Algorithm. The challenge in building this system was to efficiently detect a Pothole present in roads, to analyze the severity of Pothole and to provide users with information like Road Quality and best possible route. We have used various algorithms for frequency-based pothole detection. We compared the results. Apart from that, we selected the best approach suitable for achieving the project goals. We have used a Simple Differentiation-based Edge Detection Algorithm for Image Processing. The system has been built on Map Interfaces for Android devices using Android Studio, which consists of usage of Image Processing Algorithm based Python frameworks which is a sub field of Machine Learning. It is backed by powerful DBMS. This project facilitates use of most efficient technology tools to provide a good user experience, real time application, reliability and improved efficiency.

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