A Real Time Vein Detection System

Ahmed, Kazi Istiaque; Habaebi, Mohamed Hadi; Islam, Rafiqul

doi:10.11591/ijeecs.v10.i1.pp129-137

Cited by 10 publications

(8 citation statements)

References 18 publications

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“…The CLAHE technique works on small areas in the image, called vamps, instead of the whole image. It then combines adjacent vamps, using bilinear interpolation to eliminate industrial boundaries; this can limit contrast, especially in homogeneous areas, to avoid noise in the image [18].…”

Section: Resultsmentioning

confidence: 99%

“…Two different imaging techniques, based on far-infrared (FIR) and near-infrared radiation [17], can be used. Vein detection systems that use FIR produce low-contrast images, rendering it difficult to distinguish veins from other components of the acquired image [18]. NIR rays penetrate the tissue easily; thus, they give clearer images than FIR [19].…”

Section: Introductionmentioning

confidence: 99%

“…Ahmed et al used an infrared camera and captured images in real-time and improved them using contrast limited adaptive histogram equalization (CLAHE); the design that was used in this system was somewhat expensive, especially since the thermal camera is expensive. In addition to this, they merely improved the image; they did not isolate the veins from the rest of the details of the captured image [18]. Prijono et al designed a system for detecting veins based on a camera and an infrared filter; they were able to isolate the veins from the rest of the image details using modified local line binary pattern (MLLBP), but the isolated veins were not accurate, and the veins were wide [22].…”

Section: Introductionmentioning

confidence: 99%

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

Alwazzan

2020

Polish Journal of Medical Physics and Engineering

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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.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Alwazzan

2020

Polish Journal of Medical Physics and Engineering

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“…Intravenous injection is difficult and painful especially for newborns, children, and obese people because appropriate veins maybe deep and not visible. The application of near-infrared light (NIR) has been a good way to help locate vein, since the light can penetrate up to several centimeters into tissues and be absorbed by the vein, which enables discrimination between blood vessels and surrounding tissues [1][2][3][4]. Based on the theory, several devices have been developed recently to aid physicians, phlebotomists and surgeons in locating veins to avoid unnecessary sticks.…”

Section: Introductionmentioning

confidence: 99%

Camera-projector calibration for near infrared imaging system

Yakno¹,

Mohamad–Saleh²,

Ibrahim³

et al. 2020

Bulletin EEI

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Advanced biomedical engineering technologies are continuously changing the medical practices to improve medical care for patients. Needle insertion navigation during intravenous catheterization process via Near infrared (NIR) and camera-projector is one solution. However, the central point of the problem is the image captured by camera misaligns with the image projected back on the object of interest. This causes the projected image not to be overlaid perfectly in the real-world. In this paper, a camera-projector calibration method is presented. Polynomial algorithm was used to remove the barrel distortion in captured images. Scaling and translation transformations are used to correct the geometric distortions introduced in the image acquisition process. Discrepancies in the captured and projected images are assessed. The accuracy of the image and the projected image is 90.643%. This indicates the feasibility of the captured approach to eliminate discrepancies in the projection and navigation images.

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“…As of now, by consistent preparing for each of the frame of the video succession, the vein portrayal for each frame is plainly being outlined as appeared in the yield as shown by [20], [21]. Conversely, in the simulational and app based real-time vein detection is also extracted in [22,23] respectively. Consequently, the clinician can recognize the vein for any sort of needle implantation to the vein all the more proficiently, errorless and easily without much of a stretch.…”

Section: Introductionmentioning

confidence: 99%

Smartphone aided real-time blood vein detection system

Ahmed¹,

Habaebi²,

Islam³

2019

Bulletin EEI

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This paper aims to develop a real-time integrated system for the detection of the blood vein utilizing an Android Mobile App. The system is intended to be a low cost solution for medical teams at clinics, emergency rooms and hosptials. The system reduces the enjuries incurred due to inaccuracies during the process of frequent needle injection when blood vein is not visible during patient’s skin inspection. Illuminated infrared light in the blood cells of the vein is absorbed due to the manifestation of the Haemoglobin in blood and the IR non-blocking camera can capture the vein patterns in the IR light spectrum. Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm was used to enhance the pattern of the vein in the Android application developed using OpenCV3. Developed system can detect the veins up to 7mm underneath of human skin in real time with a frame rate of 25fps. This is a far better improvement than commercial systems that can detect veins only below 10mm underneath the skin. Moreover, this system not only focused on needle infusion but also it can be used to indicate the place of bleeding for the clots from the human body strokes, etc. in the upper layer of skin. It can also be used to detect measure liquids in encapsulated in confined dark bottles, for example, liquid chemical pouring into the bottles in the chemical companies, liquid medicine pouring to bottles, etc. The system can be further developed to detect skin infection and other dermatological diseases underneath the skin.

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A Real Time Vein Detection System

Cited by 10 publications

References 18 publications

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

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

Camera-projector calibration for near infrared imaging system

Smartphone aided real-time blood vein detection system

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