Development of Low Cost System for Estimating RBC, WBC Count Using Image Processing

2021 ◽  
Vol 11 (1) ◽  
pp. 26-38
Author(s):  
Rajithkumar B. K. ◽  
Shilpa D. R. ◽  
Uma B. V. ◽  
H. S. Mohana
Keyword(s):  
Image Processing ◽  
Low Cost ◽  
Detection Algorithm ◽  
The Body ◽  
Cost Estimating ◽  
Vector Borne Diseases ◽  
Cost System ◽  
Canny Edge ◽  
Wbc Count ◽  
Processing Techniques

Blood-related diseases are one of the most widespread and rampant vector-borne diseases in tropical countries like India. With an ever-increasing population and enormous stress on resources like land and water, new avenues open for insects like mosquitoes to breed and propagate the virus. The traditional lab method for the detection of diseases in a human's anatomy involves extracting the blood and subjecting it to various tests to count and detect the number of blood cells. An abnormally low platelet count would indicate the presence of the virus in the body. The usual method undertaken by labs all over the world is the use of the conventional chemical procedures, which may take a few hours to produce the result. The proposed system for the low cost estimating of RBC and WBC is developed using image processing techniques and canny edge detection algorithm. The obtained results are analysed and compared with the conventional methods, and results are obtained with an accuracy of 91.2.

Lung Cancer Detection using Image Processing Techniques and its Classification

2021 ◽  
Vol 9 (9) ◽  
pp. 1578-1583
Author(s):  
Aishwarya .R
Keyword(s):  
Lung Cancer ◽  
Image Processing ◽  
Support Vector Machine ◽  
Cell Carcinoma ◽  
Mortality Rates ◽  
The Body ◽  
Support Vector ◽  
Lung Tumour ◽  
Image Processing Techniques ◽  
Processing Techniques

Abstract: Lung cancer has been a major contribution to mortality rates world-wide for many years now. There is a need for early diagnosis of lung cancer which if implemented, will help in reducing mortality rates. Recently, image processing techniques have been widely applied in various medical facilities for accurate detection and diagnosis of abnormality in the body images like in various cancers such as brain tumour, breast tumour and lung tumour. This paper is a development of an algorithm based on medical image processing to segment the lung tumour in CT images due to the lack of such algorithms and approaches used to detect tumours. The work involves the application of different image processing tools in order to arrive at the desired result when combined and successively applied. The segmentation system comprises different steps along the process. First, Image preprocessing is done where some enhancement is done to enhance and reduce noise in images. In the next step, the different parts in the images are separated to be able to segment the tumour. In this phase threshold value was selected automatically. Then morphological operation (Area opening) is implemented on the thresholded image. Finally, the lung tumour is accurately segmented by subtracting the opened image from the thresholded image. Support Vector Machine (SVM) classifier is used to classify the lung tumour into 4 different types: Adenocarcinoma(AC), Large Cell Carcinoma(LCC) Squamous Cell Carcinoma(SCC), and No tumour (NT). Keywords: Lung tumour; image processing techniques; segmentation; thresholding; image enhancement; Support Vector Machine; Machine learning;

Fast and Robust Vision System for Shogi Robot

2015 ◽  
Vol 27 (2) ◽  
pp. 182-190
Author(s):  
Gou Koutaki ◽  
◽  
Keiichi Uchimura
Keyword(s):  
Image Processing ◽  
Vision System ◽  
Low Cost ◽  
Robot Arm ◽  
Image Processing Algorithm ◽  
Robot System ◽  
Cost System ◽  
Robot Systems ◽  
Web Camera ◽  
Lower Frame

<div class=""abs_img""> <img src=""[disp_template_path]/JRM/abst-image/00270002/08.jpg"" width=""150"" />Developed shogi robot system</div> The authors developed a low-cost, safety shogi robot system. A Web camera installed on the lower frame is used to recognize pieces and their positions on the board, after which the game program is played. A robot arm moves a selected piece to the position used in playing a human player. A fast, robust image processing algorithm is needed because a low-cost wide-angle Web camera and robot are used. The authors describe image processing and robot systems, then discuss experiments conducted to verify the feasibility of the proposal, showing that even a low-cost system can be highly reliable. </span>

Method for fluorescence image processing for low cost system

2016 ◽  
Author(s):  
Z. Asrih ◽  
A. El Mourabit ◽  
I. El Hajjouji ◽  
A. Ezzine ◽  
Y. Laaziz ◽  
...  
Keyword(s):  
Image Processing ◽  
Low Cost ◽  
Fluorescence Image ◽  
Cost System

scholarly journals Algorithm to Image Identification and Artix-7 FPGA Implementation for Adequate Edge Detection.

2020 ◽  
Vol 8 (5) ◽  
pp. 1656-1660
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Detection Algorithm ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
Low Contrast ◽  
Image Identification ◽  
Canny Edge ◽  
Set Up ◽  
Canny Edge Detection Algorithm

For any image identification based applications, edge detection is the primary step. The intention of the edge detection in image processing is to minimize the information that is not required in the analysis of identification of an image. In the process of reduction of insignificant data in the image, it may lead to some loss in information which in turn raise some problems like missing of boundaries with low contrast, false edge detection and some other noise affected problems. In order to reduce the effects due to noise, a modified version of popular edge detection algorithm “Canny edge detection algorithm” is proposed. Artix 7 FPGA board set up is used to implement, by using Xilinx platform the image that is obtained as output is displayed on monitor which is connected with FPGA board using connector port DVI. MATLAB Simulink is used for algorithm simulation and then it is executed on FPGA board using Xilinx platform. The results provide good motivation to use in different edge detection applications.

scholarly journals Quantum-Assisted Retinal Drusen Detection Algorithm using Entropy-Based Image Processing Techniques

2020 ◽  
Vol 9 (3) ◽  
pp. 2251-2256
Keyword(s):  
Image Processing ◽  
Composite System ◽  
Detection Method ◽  
Research Work ◽  
Detection Algorithm ◽  
Image Processing Techniques ◽  
Sensitivity Specificity ◽  
Processing Techniques ◽  
Retinal Fundus ◽  
Retinal Drusen

Drusen identification is the fundamental operation in the automated diagnosis of eye diseases. Manual and automatic detection of the drusen in the retinal fundus images has been developed recently in the classical manner only. This work provides the quantum-based retinal drusen detection method using entropy-based image processing techniques. This algorithm is the composite system of two channels, classical and quantum channels for the preprocessing and drusen detection respectively. This research work has been evaluated with the databases of DRIVE, STARE, MESSIDOR, E-Optha-Ex and ONH-Hunter. This quantum-based approach will be analyzed with the results of the existing classical methods and proves its efficiency from the calculations of sensitivity, specificity, accuracy and execution time.

scholarly journals Automatic Detection of Optic Disc for Diabetic Retinopathy

2020 ◽  
Vol 9 (7) ◽  
pp. 1013-1015
Keyword(s):  
Image Processing ◽  
Diabetic Retinopathy ◽  
Optic Disc ◽  
Early Stage ◽  
Vital Role ◽  
Retinal Images ◽  
Image Processing Techniques ◽  
Canny Edge ◽  
Total Blindness ◽  
Processing Techniques

Diabetic Retinopathy affects the retina of the eye and eventually it may lead to total visual impairment. Total blindness can be avoided by detecting Diabetic Retinopathy at an early stage. Various manual tests are used by the doctors to detect the presence of disease, but they are tedious and expensive. Some of the features of Diabetic Retinopathy are exudates, haemorrhages and micro aneurysms. Detection and removal of optic disc plays a vital role in extraction of these features. This paper focuses on detection of optic disc using various image processing techniques, algorithms such as Canny edge, Circular Hough (CHT). Retinal images from IDRiD, Diaret_db0, Diaret_db1, Chasedb and Messidor datasets were used.

scholarly journals Detecção de Vagas em Estacionamento Usando Visão Computacional e Redes Neurais Convolucionais

2020 ◽  
Author(s):  
Caroline Mazetto Mendes ◽  
Willian Marrion Cavenagli
Keyword(s):  
Image Processing ◽  
Detection Algorithm ◽  
Parking Space ◽  
Urban Mobility ◽  
Parking Lots ◽  
Image Processing Techniques ◽  
Mobility Problem ◽  
Processing Techniques

Parking lots are no longer practical solutions but become anothertopic of urban mobility problem due to the difficulty in finding availableparking spaces. This work proposes a parking space detectionsystem to assist drivers. The system detects unoccupied vacanciesby image processing techniques and convolutional neural networks.Vacancies are detected through horizontal markings and by recognizingspaces with or without vehicles. Finally, a mobile applicationmakes available to the user the occupancy status of vacancies. Initialresults showed that the system detects vacancies with visiblemarkings during the daytime. To improve detection in adversesituations, the vacancy detection algorithm is being improved.

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