scholarly journals Development of Conventional Controller Based on Image Processing for Monitoring and Controlling Burning Zone Temperature in a Cement Plant in Rotary Kiln Process Through IOT

2021 ◽  
Vol 20 (4) ◽  
pp. 209-214
Author(s):  
Polaiah Bojja ◽  
N. Merrin Prasanna ◽  
Pamula Raja Kumari ◽  
T. Bhuvanendhiran ◽  
Panuganti Jayanth Kumar
Keyword(s):  
Image Processing ◽  
Rotary Kiln ◽  
Continuous Process ◽  
Color Space ◽  
Threshold Value ◽  
Cement Industry ◽  
Raspberry Pi ◽  
Python Language ◽  
Burning Zone ◽  
Processing Techniques

In the cement factories, a rotary kiln is a pyro-processing device that is used to raise the temperature of the materials in a continuous process. Temperature monitoring is an essential process in the rotary kiln to yield high quality clinker and it has been implemented using various image processing techniques. In this paper we are measuring and controlling the temperature of rotational kiln in cement industry to get proper clinker ouput. Burning zone flame images are captured using CCD(Charge Coupled Device) camera and are processed using image processing with PID(Proportion Integration and Derivative) controller and which are programmed on raspberry pi card with the help of python language, also the captured images and attributes are transferred to authorized mobile/pc through Raspberry PI by selecting the IP address of mobile or PC. All the attributes received in the mobile in the form of web page the according to the object following data temperature controlled and object is ceaselessly followed to get the proper clinker output. Picture handling calculation with Open cv, as indicated by the calculation the edge estimation of the camera is settled. The frame value of the camera is set. Conversion from RGB color space to HSV color space is achieved and the reference color threshold value is determined. The range esteem estimated by the camera is contrasted and the reference esteem. In this study temp of rotational kiln is measured effectively using PID controller, this controller continuously control the temperature of revolving kiln by varying the i/p images of burning zone at finally fix one flame which is giving 1400degc.

scholarly journals Development and Evaluation of Mathematical Model based Region of Interest for Rotary kiln Burning Zone Temperature in Cement Industry by Digital Image Processing

2019 ◽  
Vol 8 (9) ◽  
pp. 3200-3208
Keyword(s):  
Mathematical Model ◽  
Image Processing ◽  
Real Time ◽  
Rotary Kiln ◽  
Region Of Interest ◽  
Cement Industry ◽  
Production Costs ◽  
Radiation Pyrometer ◽  
Burning Zone ◽  
Zone Temperature

Industrial processes particularly cement manufacturing unit consumes about 7% of total fuel used in the industry and hence there are strenuous efforts to reduce the fuels and lower the production costs by applying Optimal Control Algorithms. In order to achieve these parameters in the Rotary Kiln Plant, we need to continuously monitor the temperatures of the burning zone inside the rotary kiln at Regions of Interest (ROI) in real-time. In this image processing setup a thermal camera samples the temperatures inside the kiln at a rate of 5 frames per 2 seconds. The images which are highly sensitive to red and green wavelengths provide sufficient resolution to differentiate between various burning temperatures. The present burning zone temperature measurement obtained from the radiation pyrometer is not reliable on the one hand and indicates temperature information about particular point in the burning zone on the other hand. This is inadequate for optimizing the operation the kiln where a kiln furnace camera has been already installed at the plant for watching the burning status the inside the kiln. Software will be developed to determine the temperature T, for the video captured from the camera. Presently real time video from the camera is displayed in a computer monitor at kiln control room. We will tap the video signal from the setup and the calculate the burning zone temperature at the Region of Interest utilizing real time Image Processing Technologies. The temperature signal so estimated will be validated using the radiation pyrometer signal obtained from the field. The graphical tool developed in MATLAB automatically converts the receiving color images to temperature measure by proposed algorithms and also interactively analyzes the temperatures in a neat graphical user interface, in less than 2 seconds duration. ROI can be selected by a movable and re-sizable window which acts like a probe on the kiln temperatures at this instant, then displays the summary statistics of the temperatures. The tool is extended to provide a real-time graph of average temperature in the ROI over a long time when the probe is fixed at a particular region. However, the developed temperature tool and the point burning zone temperature measured by a proposed mathematical model as like thermocouple in the plant. The results are carried out by MATLAB software and benefits will be quantified in terms of enhancement in the Production efficiency, Energy efficiency, Pollution Control and clean environment.

scholarly journals IDENTIFICATION OF MEGALOBLASTIC ANEMIA CELLS THROUGH THE USE OF IMAGE PROCESSING TECHNIQUES

2018 ◽  
Vol 4 (3) ◽  
pp. 1-5 ◽  
Author(s):  
Asaad Babker ◽  
Vyacheslav Lyashenko
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Blood Smear ◽  
Color Image ◽  
Megaloblastic Anemia ◽  
Cell Structure ◽  
Color Space ◽  
Image Processing Techniques ◽  
Processing Techniques ◽  
Blood Smear Image

Objective: Our aim is to show the possibility of using different image processing techniques for blood smear analysis. Also our aim is to determine the sequence of image processing techniques to identify megaloblastic anemia cells. Methods: We consider blood smear image. We use a variety of image processing techniques to identify megaloblastic anemia cells. Among these methods, we distinguish the modification of the color space and the use of wavelets. Results: We developed a sequence of image processing techniques for blood smear image analysis and megaloblastic anemia cells identification. As a characteristic feature for megaloblastic anemia cells identification, we consider neutrophil image structure. We also use the morphological methods of image analysis in order to reveal the nuclear lobes in neutrophil structure. Conclusion: We can identify the megaloblastic anemia cells. To do this, we use the following sequence of blood smear image processing: color image modification, change of the image contrast, use of wavelets and morphological analysis of the cell structure. 

Application of thresholding algorithms for brown bread porosity evaluation

2019 ◽  
Vol 2 (2) ◽  
pp. 99
Author(s):  
Angel Danev ◽  
Atanaska Bosakova-Ardenska ◽  
Miroslav Apostolov
Keyword(s):  
Image Processing ◽  
Threshold Value ◽  
Physicochemical Parameter ◽  
Fast Evaluation ◽  
Real Time Processing ◽  
Global Threshold ◽  
Java Program ◽  
Computer Based ◽  
Brown Bread ◽  
Processing Techniques

The bread is one of the most popular foods in Bulgaria. It’s quality is regulated by approved standards. This paper presents a computer based approach for evaluation of bread porosity which is one of physicochemical parameters of bread quality. The proposed approach includes image processing techniques. A Java program is developed to binarize images of bread and calculate ratio of white pixels to all (coefficient of diversity). This coefficient corresponds with physicochemical parameter- bread porosity. It is used an open-source plugin Auto_Threshold for image binarization. This plugin implements seventeen different algorithms to find global threshold value of a grayscale image. The results show that global thresholding is appropriate for evaluation of bread porosity. The correlation analysis shows that algorithm HisAnalysis could be used for fast and effective evaluation of bread porosity using image processing. Practical applicationsThe use of image processing accelerate the process of bread porosity evaluation. Presented research proves practical benefit to apply image processing for evaluation of physicochemical parameter- bread porosity. The results show that seven algorithms which are included in Auto_Threshold plugin and HisAnalysis algorithm are suitable for bread porosity evaluation. The fastest algorithm is HisAnalysis and it could be used in practice for fast evaluation (in real-time processing) of physicochemical parameter- bread porosity.

scholarly journals A Systematic Investigation of Models for Color Image Processing in Wound Size Estimation

Computers ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 43
Author(s):  
Filipe Ferreira ◽  
Ivan Miguel Pires ◽  
Mónica Costa ◽  
Vasco Ponciano ◽  
Nuno M. Garcia ◽  
...  
Keyword(s):  
Image Processing ◽  
Size Structure ◽  
Color Image ◽  
Color Space ◽  
Quantitative Information ◽  
Systematic Investigation ◽  
Size Estimation ◽  
Wound Area ◽  
Computerized Image Processing ◽  
Processing Techniques

In recent years, research in tracking and assessing wound severity using computerized image processing has increased. With the emergence of mobile devices, powerful functionalities and processing capabilities have provided multiple non-invasive wound evaluation opportunities in both clinical and non-clinical settings. With current imaging technologies, objective and reliable techniques provide qualitative information that can be further processed to provide quantitative information on the size, structure, and color characteristics of wounds. These efficient image analysis algorithms help determine the injury features and the progress of healing in a short time. This paper presents a systematic investigation of articles that specifically address the measurement of wounds’ sizes with image processing techniques, promoting the connection between computer science and health. Of the 208 studies identified by searching electronic databases, 20 were included in the review. From the perspective of image processing color models, the most dominant model was the hue, saturation, and value (HSV) color space. We proposed that a method for measuring the wound area must implement different stages, including conversion to grayscale for further implementation of the threshold and a segmentation method to measure the wound area as the number of pixels for further conversion to metric units. Regarding devices, mobile technology is shown to have reached the level of reliable accuracy.

scholarly journals DESIGN AND IMPLEMENTATION OF ANTI-TANK GUIDED-MISSILE (ATGM) CONTROL SYSTEM USING SEMI-AUTOMATIC COMMAND LINE OF SIGHT (SACLOS) METHOD BASED ON DIGITAL IMAGE PROCESSING

2021 ◽  
Vol 7 (2) ◽  
pp. 217
Author(s):  
Muhammad Hanifudin Al Fadli ◽  
Dadang Gunawan ◽  
Romie Oktovianus Bura ◽  
Larasmoyo Nugroho
Keyword(s):  
Image Processing ◽  
Control System ◽  
Tracking System ◽  
Color Space ◽  
Raspberry Pi ◽  
Infrared Lamp ◽  
Syrian Civil War ◽  
High Level ◽  
Infrared Tracking ◽  
Coordinate Data

<div><p class="Els-history-head">The Anti-Tank Guided-Missile (ATGM) system has a very important role in the modern battlefield. This system proved its effectiveness in many modern conflicts such as the Syrian Civil War and Nagorno-Karabakh War. The ATGM system has a very simple electronic and mechanism but it has a very high level of accuracy and precision. One of the control methods used in ATGM is SACLOS method. This method tracks missile position by detecting an infrared lamp that is placed on the missile tail. The tracking system sends control signals to the missile as a result of the correction of the missile position when flying. The infrared tracking system in this research was made using a modified OV5647 camera with the addition of a 940 nm narrow bandpass filter. There are 3 cameras with 1x, 8x, and 16x magnifications which are accessed using 3 Raspberry Pi boards. X and y coordinate data of the infrared lamp is sent to the airframe using wireless telemetry. Atmega328 microcontroller process x and y coordinate data into input proportional control. The result of this research is the prototype of an anti-tank missile control system with an infrared tracking instrument capable track a series of 88 infrared LEDs as far as 997.16 meters with a tracking speed of 90.11 FPS. The threshold parameters of image processing using luminance of YUV color space has a range of 240-255. The control parameter Kp=7 is used in wind tunnel testing with airspeed 20 m/s capable of directing airframe motion to the telescope's crosshairs.</p></div>

scholarly journals De-Noising of Uterus Fibroid Ultrasound Image Using Gaussismooth Convolution Filter (GSCF)

2020 ◽  
Vol 5 (7) ◽  
pp. 1033-1037
Author(s):  
Dr. M. Renuka Devi ◽  
V. Sindhu
Keyword(s):  
Image Processing ◽  
Imaging Techniques ◽  
Ultrasound Image ◽  
Cost Effective ◽  
Initial Step ◽  
Threshold Value ◽  
Input Image ◽  
Local Maxima ◽  
Convolution Filter ◽  
Processing Techniques

This paper discusses the methods to detect the presence of uterus fibroid in woman by implementing various image processing techniques. The input image is an ultrasound image as it is cost effective when compared to other imaging techniques like CT, MRI. The initial step in image processing is to remove noise by applying filters. Application of filters smoothen the image without blurring the image. Gradient of the processed image is calculated and the image is enhanced by sharpening the edges of the image are achieved by calculating the local maxima of the gradient. Then, the edges are decided by calculating the threshold value of the processed image. The proposed Gaussismooth Convolution Filter gives better results when compared with other existing filter with PSNR value of 94%.

scholarly journals Automated Segmentation of Leukocytes using Marker-based Watershed Algorithm from Blood Smear Images

2021 ◽  
Author(s):  
Vipasha Abrol ◽  
Sabrina Dhalla ◽  
Jasleen Saini ◽  
Ajay Mittal ◽  
Sukhwinder Singh ◽  
...  
Keyword(s):  
Image Processing ◽  
Blood Smear ◽  
White Blood Cells ◽  
Color Space ◽  
Specific Marker ◽  
Watershed Algorithm ◽  
Hsv Color Space ◽  
Whole Process ◽  
Proposed Model ◽  
Processing Techniques

The aim of this paper is to perform segmentation of white blood cells (WBCs) using blood smear images with the help of image processing techniques. Traditionally, the process of morphological analysis of cells is performed by a medical expert. This process is quite tedious and time consuming. The equipments used to perform the experiments are very costly and might not be available in all hospitals. Further, the whole process is quite lengthy and prone to error easily because of the lack of standard set of procedure. Hence there is a need for innovative and efficient techniques. An automated image segmentation system can make the blood test process much easier and faster. Segmentation of a nucleus image is one of the most critical tasks in a leukemia diagnosis. In this work, we have investigated and implemented image processing algorithms to segment cells. The proposed model detects WBCs and converts cell images from RGB to HSV color space using Otsu thresholding. The resultant image is then processed with the morphological filter because the segmented image contains noise which affects the system performance. Lastly, the Marker-based watershed algorithm is implemented in which specific marker positions are defined. The proposed model is tested on publically available ALL-IDB2 dataset. The system’s performance was overall examined and resulted in 98.99% overall precision for WBC segmentation.

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