Current Issue : January-March Volume : 2024 Issue Number : 1 Articles : 5 Articles
We suggest two steps of reducing the amount of data transmitted on Internet of Vehicle networks. The first step shifts the image from a full-color resolution to only an 8-color resolution. The reduction of the color numbers is noticeable; however, the 8-color images are enough for the requirements of common vehicles’ applications. The second step suggests modifying the quantization tables employed by H.264 to different tables that will be more suitable to an image with only 8 colors. The first step usually reduces the size of the image by more than 30%, and when continuing and performing the second step, the size of the image decreases by more than 40%. That is to say, the combination of the two steps can provide a significant reduction in the amount of data required to be transferred on vehicular networks....
SD Muhammadiyah Sangonan 1 has implemented fingerprint attendance, where teachers and staff record their attendance when they arrive and leave. Attendance records are still manually recorded by administrative personnel, and attendance reporting is limited to attendance recapitulation. In short, the efficiency of managing teacher and staff attendance administration is still low. Therefore, this research aims to improve the efficiency of teacher and staff administration through the implementation of image processing technology for fingerprint attendance. The planned stages of the research are planning, fingerprint attendance system development, administration system training, and program evaluation. In its implementation, this program has proven to be effective in improving the effectiveness of SD Muhammadiyah Sangonan 1 Godean's school administration in terms of easier and faster attendance data processing. The outputs achieved include mass media news and videos....
Image processing techniques are based nearly exclusively on RGB (red–green–blue) representation, which is significantly influenced by technological issues. The RGB triplet represents a mixture of the wavelength, saturation, and lightness values of light. It leads to unexpected chromaticity artifacts in processing. Therefore, processing based on the wavelength, saturation, and lightness should be more resistant to the introduction of color artifacts. The proposed process of converting RGB values to corresponding wavelengths is not straightforward. In this contribution, a novel simple and accurate method for extracting the wavelength, saturation, and lightness of a color represented by an RGB triplet is described. The conversion relies on the known RGB values of the rainbow spectrum and accommodates variations in color saturation....
In hyperspectral unmixing (HU), spectral variability in hyperspectral images (HSIs) is a major challenge which has received a lot of attention over the last few years. Here, we propose a method utilizing a generative adversarial network (GAN) for creating synthetic HSIs having a controllable degree of realistic spectral variability from existing HSIs with established ground truth abundance maps. Such synthetic images can be a valuable tool when developing HU methods that can deal with spectral variability. We use a variational autoencoder (VAE) to investigate how the variability in the synthesized images differs from the original images and perform blind unmixing experiments on the generated images to illustrate the effect of increasing the variability....
As healthcare costs continue to rise, finding affordable and non-invasive ways to monitor vital signs is increasingly important. One of the key metrics for assessing overall health and identifying potential issues early on is respiratory rate (RR). Most of the existing methods require multiple steps that consist of image and signal processing. This might be difficult to deploy on edge devices that often do not have specialized digital signal processors (DSP). Therefore, the goal of this study is to develop a single neural network realizing the entire process of RR estimation in a single forward pass. The proposed solution builds on recent advances in video recognition, capturing both spatial and temporal information in a multi-path network. Both paths process the data at different sampling rates to capture rapid and slow changes that are associated with differences in the temperature of the nostril area during the breathing episodes. The preliminary results show that the introduced end-to-end solution achieves better performance compared to state-of-the-art methods, without requiring additional pre/post-processing steps and signal-processing techniques. In addition, the presented results demonstrate its robustness on low-resolution thermal video sequences that are often used at the embedded edge due to the size and power constraints of such systems. Taking that into account, the proposed approach has the potential for efficient and convenient respiratory rate estimation across various markets in solutions deployed locally, close to end users....
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