12/18/2023 0 Comments Spider veins create diffraction spikes![]() The algorithm contains several fundamental steps that are discussed under the methodological approach and extensively under the Implementation section. This task is a bit complex as we need to develop an algorithm that is capable of performing this task both efficiently and accurately. Here, we isolate only the vein pattern from the body part captured in the image and that will be used as the image that is displayed on the screen. 3.1.4 Applying a formulated algorithm to clearly visualize and extract the vein patternsĪfter preprocessing, we focus on extracting the region of interest from the image. The same preprocessing procedures are implemented for video capturing as well. The main objective is to create a visible contrast between the Region of Interest and its surroundings. These steps utilize image processing techniques to enhance the region of interest in a captured image (for example, the vein pattern in hand). Once an image is acquired, preprocessing steps are applied. Later on, we progress to capturing a live stream instead of a still image. For this purpose, we use a modified CMOS camera and, with the help of the light source, illuminate the object of interest and capture it. Once the light sources were selected, we proceeded with the capturing of images. This step is a prerequisite for image capturing. Here, we determined parameters such as the optimum wavelength, intensity,Īnd lighting conditions, thereby the environment where image capturing should occur and the placement of the object. We obtained a variety of different sources of the near IR region. 3.1.1 Identifying the optimum wave length for lighting and obtain the appropriate light sources The overall procedure can be divided into a few basic sub-components. The entire process – detection and display occur in real-time. Our task is to design and develop a device capable of detecting veins belonging to a particular region and display them on a portable screen accurately. Our plan is to conduct a clinical trial and test the device on human subjects and get the feedback from both the patients and phlebotomists and improve the model so that those final users are satisfied. We have concluded that a higher intensity does not always increase the visibility of veins. In order to quantitatively analyze, we have obtained a count of the number of visible veins and depicted the comparison in a graph. We have also analyzed how the results vary based on body fat. We have tested the prototype using different combinations of light sources with different intensities and have analyzed the results. We display the vein map on a 7 inch IPS LCD screen. Initially, we processed the still images and later on developed the model to process the live video stream and display the processed video footage that visualizes the veins in real-time. Images are processed using OpenCV, and Histogram equalization and CLAHE algorithms are used in preprocessing. We use near-infrared LEDs as the source of illumination, and a CMOS camera for image acquisition. We have tested and optimized the algorithms accordingly. The low-cost is achieved by optimizing the image processing algorithms and adjusting the illumination method. We decided on using this technique after assessing both the available techniques. We propose a low-cost mechanism of obtaining near-infrared spectroscopy by using the image-guided technique. Some of the available devices use image-guided venipuncture technique and the others use projection. While there exist a few models which use the said mechanism, these models are costly, have accuracy issues, and are limited only to certain types of skin tones. ![]() Near-Infrared spectroscopy is used for better vein visualization to make the venipuncture process more efficient. ![]()
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