Application of Image Processing and Fuzzy Logic to Mobile Robots Providing Assistance to Fire Fighters

2013 ◽  
Vol 389 ◽  
pp. 740-746
Author(s):  
Ayman Abbas ◽  
Khaled El-Geneidy
Keyword(s):  
Image Processing ◽  
Feature Detection ◽  
Robot Vision ◽  
Region Of Interest ◽  
Influential Factors ◽  
Fire Fighting ◽  
Fire Fighters ◽  
Image Processing Techniques ◽  
Image Processing Algorithms ◽  
Processing Techniques

The motive behind this research project is to devise a method for overcoming some of the challenges faced by fire fighters in Egypt while accomplishing their duties. This is achieved by utilizing robot vision technology as one of the approaches used for task automation. Based on a study of different methods of automation in human tracking and fire fighting applications, image processing techniques with the highest potential in a fire fighting environment were identified. A system has been developed which fusses the selected image processing algorithms with fuzzified readings from distance sensors, to extract the major blue areas in acquired images that is more likely to correspond to the uniform worn by fire fighters in Egypt. Subsequently the extracted blue area is used to identify a region of interest within the image in order to reduce the computations. The feature detection process constrains its search for a feature found on the back of the target fire fighter to the identified region of interest. Based on the location and area of this feature, the system will calculate the required velocity components to control the motion of the robot and the camera pan and tilt mechanism, in order to continue tracking the target along its path. The system has been validated by conducting an experiment which simulates the key influential factors in a fire fighting environment.

Method for Estimating the Manual Nesting Process Efficiency for Profiling Machines, Based upon Image Processing Techniques

2015 ◽  
Vol 808 ◽  
pp. 86-91
Author(s):  
Radu Eugen Breaz ◽  
Octavian Bologa ◽  
Sever Gabriel Racz
Keyword(s):  
Image Processing ◽  
Software Package ◽  
Process Efficiency ◽  
Matlab Software ◽  
Image Processing Techniques ◽  
Graphic File ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Processing Techniques

The paper presents a method for estimating the efficiency of the manual nesting process. By using the graphic file generated during the nesting process and using image processing techniques, the method allows the user to calculate the percentage of material used for manufacturing the parts. The method combines a manual approach - the user has to select some specific points on the graphic file with the mouse, with some image processing algorithms form Matlab software package.

scholarly journals Automated detection of vehicles license plate using image processing techniques

2020 ◽  
Vol 18 (3) ◽  
pp. 1408
Author(s):  
Farhana Ahmad Poad ◽  
Noor Shuraya Othman ◽  
Roshayati Yahya Atan ◽  
Jusrorizal Fadly Jusoh ◽  
Mumtaz Anwar Hussin
Keyword(s):  
Image Processing ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Region Of Interest ◽  
Automated Detection ◽  
License Plate ◽  
Image Processing Techniques ◽  
Individual Character ◽  
Split And Merge ◽  
Processing Techniques

The aim of this project is to design an Automated Detection of License Plate (ADLP) system based on image processing techniques. There are two techniques that are commonly used in detecting the target, which are the Optical Character Recognition (OCR) and the split and merge segmentation. Basically, the OCR technique performs the operation using individual character of the license plate with alphanumeri characteristic. While, the split and merge segmentation technique split the image of captured plate into a region of interest. These two techniques are utilized and implemented using MATLAB software and the performance of detection is tested on the image and a comparison is done between both techniques. The results show that both techniques can perform well for license plate with some error.

scholarly journals Detection of Cotton Leaf Disease Using Image Processing Techniques

2021 ◽  
Vol 2062 (1) ◽  
pp. 012009
Author(s):  
Sushreeta Tripathy
Keyword(s):  
Image Processing ◽  
Plant Disease ◽  
Region Of Interest ◽  
Texture Features ◽  
Disease Diagnosis ◽  
Cotton Leaf ◽  
Diagnosis System ◽  
Image Processing Techniques ◽  
Plant Disease Diagnosis ◽  
Processing Techniques

Abstract In the area of research, diagnosis of disease symptoms in the plants duly applying image processing methods is a matter of big concern. The need of the hour is to prepare an efficient plant disease diagnosis system that can help the farmers in their cultivation and farming. This work is an attempt to prepare a framework of plant disease diagnosis system by using the cotton plant leaves. The digital pictures of cotton leaves are obtained to undergo a set of image processing techniques. Thresholding based segmentation techniques are used to remove the region of interest (ROI) i.e., infected part from the enhanced images. Consequently, diseases are detected from the region of interest by using an accurate set of visual texture features. At last treatment actions are taken to supervise the diseases found in the plants. This work will help the farmer’s society to take effective measures to protect their crops from diseases.

scholarly journals Comparative analysis of image processing techniques for obstacle avoidance and path deduction

2021 ◽  
Vol 2070 (1) ◽  
pp. 012121
Author(s):  
R Rajavarshini ◽  
S Shruthi ◽  
P Mahanth ◽  
Boddu Chaitanya Kumar ◽  
A Suyampulingam
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Obstacle Avoidance ◽  
Transportation System ◽  
Image Processing Algorithm ◽  
Image Processing Techniques ◽  
Haar Cascade ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Processing Techniques

Abstract The growing need for automation has a significant impact on our daily lives. Automating the essentials of our society like transportation system has plenty of applications like unmanned ground vehicles in military, wheel chair for disabled, domestic robots, etc., There are driving, braking, obstacle tackling etc., to a transportation system that can be automated. This paper particularly focuses on automating the obstacle avoidance which provides intelligence to the vehicle and ensures a high degree of safety and is performed using image processing algorithms. Edge based detection, image segmentation, and Machine Learning based method are the three image processing techniques used to detect and avoid obstacles. Haar cascade classifier is the machine learning method where Haar cascade analysis is performed for better accurate results with justifying graphs and parametric values obtained. A comparison of the three image processing algorithms is also tabulated considering obstacle size, colour, familiarities and environmental lightings and the best image processing algorithm is inferred.

scholarly journals Image Processing Techniques Based Crowd Size Estimation

2020 ◽  
Vol 12 (3) ◽  
pp. 407-414
Author(s):  
Mohanad Abdulhamid ◽  
◽  
Lwanga Wanjira ◽  
Keyword(s):  
Image Processing ◽  
Theoretical Foundation ◽  
Visual Basic ◽  
Size Estimation ◽  
Image Processing Techniques ◽  
Development Tools ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
High Level ◽  
Processing Techniques

Image processing algorithms are the basis for image computer analysis and machine Vision. Employing a theoretical foundation, image algebra, and powerful development tools, Visual C++, Visual Fortran, Visual Basic, and Visual Java, high-level and efficient computer vision techniques have been developed. This paper analyzes different image processing algorithms by classifying them in logical groups. In addition, specific methods are presented illustrating the application of such techniques to the real world images. In most cases more than one method is used. This allows a basis for comparison of different methods as advantageous features as well as negative characteristics of each technique is delineated. The main objective of this paper is to use image processing techniques to estimate the size of a crowd from a still photograph. The simulation results show that the different images have different efficiencies.

scholarly journals Mendeteksi Kondisi Organ Liver Melalui Citra Iris Menggunakan Teknik Pengolahan Citra Digital (Detecting the Condition of Liver Organ Through Iris Image Using Digital Image Processing Techniques)

2019 ◽  
Vol 3 (1) ◽  
pp. 138 ◽  
Author(s):  
Maxima Ari Saktiono
Keyword(s):  
Image Processing ◽  
Processing System ◽  
Region Of Interest ◽  
Video Camera ◽  
Visual Basic ◽  
The Body ◽  
Physical Test ◽  
Image Processing Techniques ◽  
Sobel Operator ◽  
Processing Techniques

Besides Physical test normally, early detection on the condition of the body by using the image processing of iris is an alternative method to observe the health of human’s body, especially the internal organ of the body. This paper uses Dr. Bernard Jensen’s chart of iris as reference, in which part and how deep is the damage happens in the tissue of iris. Organ disorder is represented by the form of broken tissue of iris. The broken tissue usually seems to be like a hole in certain area in the iris. In this paper, the instrumentation for data mining uses video camera and the software that will be developed uses Visual Basic on image processing programming. In the image of eye, the region of interest is only on the iris, and it will be grabbed by using circle and line equations.The area of Liver organ lies on 07.15 – 07.45 in the third Quadran. After wards, this slice of image is prepared for image processing system. The method that is going to be used in this paper is grey level, enhancing and sobel operator. Then, the output of the system will be compared with physical test to measure the precision on detecting the problem on Liver organ.

scholarly journals An Exploration of the Image Processing Techniques for the Detection of Leukemia

2018 ◽  
Vol 7 (2) ◽  
pp. 96-99
Author(s):  
A. Premnath ◽  
V. S. Meenakshi
Keyword(s):  
Image Processing ◽  
Bone Marrow ◽  
Blood Cell ◽  
Diagnostic Method ◽  
Cell Classification ◽  
Image Processing Techniques ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Processing Techniques

In the pathological diagnostic method, categorization of blood cell has more essential to detect and analyze the disease. The complications that are connected with blood can be distributed only after the blood cell classification. The illness that begins with the bone marrow is the Leukemia. Therefore, it must be handled at the beginning step and proceeds to death if continuing untreated. This present research elucidates an investigation of diagnosing leukemia from microscopic blood image exhausting various image processing algorithms.

Development of a Hybrid Technique Utilising Image Processing and Fuzzy Logic for Dynamically Detecting a Movable Colour Object

2013 ◽  
Vol 389 ◽  
pp. 734-739
Author(s):  
Ayman Abbas ◽  
Khaled El-Geneidy
Keyword(s):  
Image Processing ◽  
Hybrid System ◽  
Mobile Object ◽  
Hybrid Technique ◽  
Autonomous Mobile Robot ◽  
Complex Environment ◽  
Image Processing Techniques ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Processing Techniques

The drive behind this research is to devise an autonomous method for dynamically detecting a movable coloured object within ambiguous environments. Based on a study of different methods of automation using image processing techniques, those with the highest potential of operating effectively and efficiently in a complex environment of varying light intensity were identified. A hybrid system has been developed which utilises the selected image processing algorithms and fuzzified readings from distance sensors, to extract an identifiable colour area in the acquired image frames. Subsequently the identified colour is used to recognise the blob area within the frame containing the moving object to be tracked. Based on the location and area of this blob, the hybrid system will dynamically identify the exact location of the target mobile object. This system mounted on an autonomous mobile robot constantly monitors the detected object.

Automatic Screening of Diabetic Maculopathy Using Image Processing

2019 ◽  
Vol 15 (4) ◽  
pp. 30-37
Author(s):  
Shweta Reddy
Keyword(s):  
Image Processing ◽  
Feature Detection ◽  
Vision Loss ◽  
Accurate Result ◽  
Screening Method ◽  
Automated System ◽  
Diabetic Maculopathy ◽  
Image Processing Techniques ◽  
Regular Screening ◽  
Processing Techniques

Retinal imaging is a challenging screening method for detection of retinal abnormalities. Diabetic Maculopathy (DM) is a condition that can result from retinopathy. Regular screening is necessary for diabetic maculopathy in order to identify the risk of vision loss. Maculopathy is damage to macula, the key region responsible for high sharp colour vision. Diabetic Retinopathy and Diabetic Maculopathy needs regular observation in order to indicate visual impairment risk. In this article, the author first presents a brief summary of diabetic maculopathy and its causes. Then, an exhaustive literature review of different automated DM diagnosis systems offered. It is important for ophthalmologists to have an automated system which detects early symptoms of the disease and yields a high accurate result. A vital assessment of the image processing techniques used for DM feature detection is projected in this paper. Various methods have been proposed to identify and classify DM based on severity level.

Three-Dimensional Structure of Rotavirus-Fab Complex

1990 ◽  
Vol 48 (1) ◽  
pp. 238-239
Author(s):  
B.V.V. Prasad ◽  
E. Marietta ◽  
J.W. Burns ◽  
M.K. Estes ◽  
W. Chiu
Keyword(s):  
Image Processing ◽  
Smooth Surface ◽  
Three Dimensional ◽  
Outer Shell ◽  
Dimensional Structure ◽  
Structural Studies ◽  
Cell Penetration ◽  
Electron Cryomicroscopy ◽  
Image Processing Techniques ◽  
Processing Techniques

Rotaviruses are spherical, double-shelled particles. They have been identified as a major cause of infantile gastroenteritis worldwide. In our earlier studies we determined the three-dimensional structures of double-and single-shelled simian rotavirus embedded in vitreous ice using electron cryomicroscopy and image processing techniques to a resolution of 40Å. A distinctive feature of the rotavirus structure is the presence of 132 large channels spanning across both the shells at all 5- and 6-coordinated positions of a T=13ℓ icosahedral lattice. The outer shell has 60 spikes emanating from its relatively smooth surface. The inner shell, in contrast, exhibits a bristly surface made of 260 morphological units at all local and strict 3-fold axes (Fig.l).The outer shell of rotavirus is made up of two proteins, VP4 and VP7. VP7, a glycoprotein and a neutralization antigen, is the major component. VP4 has been implicated in several important functions such as cell penetration, hemagglutination, neutralization and virulence. From our earlier studies we had proposed that the spikes correspond to VP4 and the rest of the surface is composed of VP7. Our recent structural studies, using the same techniques, with monoclonal antibodies specific to VP4 have established that surface spikes are made up of VP4.

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