scholarly journals Low cost blood vein detection system based on near-infrared LEDs and image-processing techniques

2020 ◽  
Vol 26 (2) ◽  
pp. 61-67
Author(s):  
Mohammed J. Alwazzan
Keyword(s):  
Image Processing ◽  
Near Infrared ◽  
Detection System ◽  
Low Cost ◽  
Ccd Camera ◽  
Accurate Identification ◽  
Image Processing Techniques ◽  
A Charge ◽  
Processing Techniques ◽  
Palm Of The Hand

AbstractDrawing blood and injecting drugs are common medical procedures, for which accurate identification of veins is needed to avoid causing unnecessary pain. In this paper, we propose a low-cost system for the detection of veins. The system emits near-infrared radiation from four light-emitting diodes (LEDs), with a charge-coupled device (CCD) camera located in the middle of the LEDs. The camera captures an image of the palm of the hand. A series of digital image-processing techniques, ranging from image enhancement and increased contrast to isolation using a threshold limit based on statistical properties, are applied to effectively isolate the veins from the rest of the image.

Automatic lung nodule detection system using image processing techniques in computed tomography

2020 ◽  
Vol 56 ◽  
pp. 101659 ◽  
Author(s):  
Chung-Feng Jeffrey Kuo ◽  
Chang-Chiun Huang ◽  
Jing-Jhong Siao ◽  
Chia-Wen Hsieh ◽  
Vu Quang Huy ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Processing ◽  
Detection System ◽  
Lung Nodule ◽  
Image Processing Techniques ◽  
Lung Nodule Detection ◽  
Nodule Detection ◽  
Processing Techniques

scholarly journals Lung Cancer Detection using Convolutional Neural Network

2019 ◽  
Vol 8 (6) ◽  
pp. 3256-3262 ◽  
Keyword(s):  
Lung Cancer ◽  
Image Processing ◽  
Detection System ◽  
Histogram Equalization ◽  
Input Image ◽  
Machine Learning Algorithms ◽  
Morphological Operations ◽  
Image Processing Techniques ◽  
Cad System ◽  
Processing Techniques

The mortality rate is increasing among the growing population and one of the leading causes is lung cancer. Early diagnosis is required to decrease the number of deaths and increase the survival rate of lung cancer patients. With the advancements in the medical field and its technologies CAD system has played a significant role to detect the early symptoms in the patients which cannot be carried out manually without any error in it. CAD is detection system which has combined the machine learning algorithms with image processing using computer vision. In this research a novel approach to CAD system is presented to detect lung cancer using image processing techniques and classifying the detected nodules by CNN approach. The proposed method has taken CT scan image as input image and different image processing techniques such as histogram equalization, segmentation, morphological operations and feature extraction have been performed on it. A CNN based classifier is trained to classify the nodules as cancerous or non-cancerous. The performance of the system is evaluated in the terms of sensitivity, specificity and accuracy

Image Processing Methodology for Determining SI Precipitate Size and Density in Oxide Layers from Conical Dark Field TEM Micrographs

2001 ◽  
Vol 7 (S2) ◽  
pp. 832-833
Author(s):  
A. Domenicucci
Keyword(s):  
Image Processing ◽  
Low Cost ◽  
Dark Field ◽  
Precipitate Size ◽  
Second Phase ◽  
Oxide Breakdown ◽  
Image Processing Techniques ◽  
Transmission Electron ◽  
The Matrix ◽  
Processing Techniques

Image processing techniques have been used for decades in many branches of science. with the advent of low cost, highresolution CCD cameras and the advances in personal computing, techniques previously used in other disciplines are increasingly being applied by transmission electron microscopists. The present paper gives an example of using image processing techniques for characterizing the number and size of second phase precipitates in an oxide matrix.Si inclusions in the form of Si precipitates can occur in silicon dioxide films. The inclusions are contained within the films and effectively reduce the local thickness of the oxide. This thinning results in a reduction in the voltage necessary to cause oxide breakdown; the larger is the precipitate, the lower the breakdown voltage. Knowledge of the precipitate size and density is therefore important when assessing the dielectric integrity of these films. The Si precipitates are crystalline and more or less randomly oriented within the matrix.

scholarly journals Fruit Quality Detection and Gradation

2021 ◽  
pp. 383-388
Author(s):  
Harshal S. Deshmukh ◽  
Dr. S. W. Mohod ◽  
Dr. N. N. Khalsa
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Detection System ◽  
Support Vector ◽  
Color Classification ◽  
Image Processing Techniques ◽  
Background Removal ◽  
Quality Detection ◽  
Analysis Methods ◽  
Processing Techniques

Grading and classification of fruits is based on observations and through experiences. The system exerts image- processing techniques for classification and grading the quality of fruits. Two-dimensional fruit images are classified on shape and color-based analysis methods. However, different fruit images have different or same color and shape values. Hence, using color or shape analysis methods are still not that much effective enough to identify and distinguish fruits images. Therefore, computer vision and image processing techniques have been found increasingly useful in the food industry, especially for applications in quality detection. Research in this area indicates the feasibility of using computer vision systems to improve product quality, the use of computer vision for the inspection of food has increased during recent years. This proposed work presents food quality detection system. The system design considers some feature that includes fruit colors and size, which increases accuracy for detection of roots pixels. Histogram of oriented gradients is used for background removal, for color classification, support vector machine is used.

scholarly journals Skin Cancer Analysis with Deep Learning

2021 ◽  
Vol 9 (VII) ◽  
pp. 2663-2672
Author(s):  
Siddharth Raj Dash
Keyword(s):  
Image Processing ◽  
Deep Learning ◽  
Skin Cancer ◽  
Medical Diagnosis ◽  
Skin Diseases ◽  
Detection System ◽  
Technological Advancement ◽  
Image Processing Techniques ◽  
The Cost ◽  
Processing Techniques

Skin diseases are some of the most common diseases and are often difficult to diagnose than other diseases. Skin diseases may be caused by fungus, bacteria, allergic reaction, viruses, cancer etc. The technological advancement in laser diagnosis and Photonics based medical diagnosis has made it possible to diagnose the skin diseases much more quickly and accurately. But the cost of diagnostics is time-consuming and very expensive. Hence, we can use image processing techniques to help build automated preliminary detection system for such dermatological diagnostics.

scholarly journals Driver Drowsiness Detection using MATLAB

2019 ◽  
Vol 8 (2) ◽  
pp. 843-844
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Detection System ◽  
Binary Image ◽  
Detection Function ◽  
Image Processing Techniques ◽  
Drowsiness Detection ◽  
Driver Drowsiness ◽  
Face Features ◽  
Processing Techniques

Drowsiness is major cause of accidents. So, this drowsiness detection system alerts the drowsy drivers in order to reduce the risk of potential accidents. The proposed system uses computer vision and image processing technology of MATLAB for detecting the drowsiness. MATLAB detects if eyes are closed or open using various image processing techniques performed using Viola-Jones face features detecting algorithm and skin y,cb,cr values detection function ,converting image into a binary image which was further employed to extract eye characteristics, and its closing frequency, determining drowsiness.

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