image and video processing applications have significant importance in many areas which are the industrial and medical applications, especially the vehicular technology. To provide safe driving, Driving Assistance Sys...
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Stable diffusion is a generative algorithm for creating images from text prompts. This paper explores prompts with color terms and proposes a process to generate, visualize and assess these results. Automated prompts ...
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imageprocessing refers to information processing techniques used with computers integrated into images in various industrial and technological fields. These techniques can be used in various applications involving th...
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ISBN:
(数字)9798350379433
ISBN:
(纸本)9798350379440
imageprocessing refers to information processing techniques used with computers integrated into images in various industrial and technological fields. These techniques can be used in various applications involving the process of object recognition and are developed within the scope of artificial intelligence. In recent years, imageprocessing techniques have been utilized in facial recognition systems to detect crime and criminals. This paper presents a study on the creation of a lie detector that provides information on whether individuals are lying by using imageprocessing techniques. For this purpose, algorithms that analyze eye blinking and emotional state behaviors from the facial region detected in the video image for lie detection were developed. These algorithms were coded in the Python programming language and combined to obtain a lie detector model. Additionally, a balanced test set consisting of video images of individuals telling the truth and lying were prepared to validate the model. In tests conducted on this set, the success rate of the obtained lie detector model was found to be 83.3%.
Hemostasis is a defence mechanism that prevents blood losses in cases of vessel injuries, and other related disorders. In many cases, patients need to frequently monitor their blood coagulation tendency in order to re...
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ISBN:
(纸本)9781665462198
Hemostasis is a defence mechanism that prevents blood losses in cases of vessel injuries, and other related disorders. In many cases, patients need to frequently monitor their blood coagulation tendency in order to regulate their medication. In addition, red blood cell aggregation (RBCA) is related to blood inflammation, and it appears elevated in many pathological conditions. Blood coagulation and RBCA can be studied by analysing the dynamic changes of light transmittance though a clotting/aggregating sample, and indeed various works in the literature exploit this approach. In this work, blood coagulation and RBCA are examined by utilising single drops of blood in an inexpensive camera-based microfluidic system, designed for low computational and production cost. Results are compared with a microscopy-camera system, with both setups utilizing the same custom made microchannel. Three imageprocessingalgorithms are developed to analyze the averaged light intensity, and the local structural chracteristics of blood, through a binarization and region classification method, using logical operations. The results illustrate the repeatability of the technique and the donorto-donor variation within the proposed approach. Based on the imageprocessing analysis, the developed coagulation and aggregation indices show great potential of utilisation in an inexpensive and robust point of care device.
PIFuHD can generate high-resolution model in the process of human 3D reconstruction. However, PIFuHD will produce debris outside the human body when the image background is more complex. In order to solve this problem...
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ISBN:
(纸本)9783031192135;9783031192142
PIFuHD can generate high-resolution model in the process of human 3D reconstruction. However, PIFuHD will produce debris outside the human body when the image background is more complex. In order to solve this problem, this paper develops an adaptive BSCO algorithm for the background of human body and image of human body in 3D reconstruction system. The BSCO algorithm is divided into four steps in processing. First, BSCO algorithm uses Go-selfies to separate the background. Second, BSCO algorithm converges the RGB of all pixels of the character into a set. Third, BSCO algorithm finds the greatest difference from the set through HSV conversion. Fourth, BSCO algorithm weighs the set and then calculates the RGB score. The highest score of RGB is used as the RGB of the background after solid color optimization. The experimental results show that the proposed method improves the reconstruction effect of PIFuHD.
Photon-counting CT (PCCT) is an emerging x-ray spectral imaging technology. There are several PCCT prototypes available for clinical and experimental applications. Despite many published results, objective quantitativ...
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ISBN:
(纸本)9781510671553;9781510671546
Photon-counting CT (PCCT) is an emerging x-ray spectral imaging technology. There are several PCCT prototypes available for clinical and experimental applications. Despite many published results, objective quantitative evaluation of PCCT systems remains challenging due to varied and unknown influences. In addition, CT acquisition geometry and imageprocessing mechanisms are often proprietary, complicating the correlations between the detector's physical characteristics and the corresponding CT image quality, hindering fair comparisons between different technologies. This study aimed to provide a resource to address these challenges by developing a versatile model that accurately replicates the physics of any semiconductor-based photon-counting detector (PCD) and integrating it into a virtual imaging framework to generate detector-specific CT images. The methodology involved a Monte Carlo simulation to model x-ray photon interactions with PCDs and an analytical Gaussian charge sharing model to model charge-diffusion and -repulsion in the detector. Finally, the energy deposited post-crosstalk by source photons (1-120 keV) in the 3x3-pixel-neighborhood was translated into photon counts across two energy thresholds to compute detector-specific spatio-energetic covariance correlation matrices. This framework was validated against experimental measurements of a clinical CdTe-based PCCT, showcasing its accuracy in reproducing real-world scenarios. Additionally, to demonstrate the model's efficacy, we simulated key PCD materials (Si, CdTe, CZT) and designed standardized scanner components, developing virtual systems (DukeCounter scanners). These systems were used to "scan" a physics phantom (ACR) and anthropomorphic-computational models (XCAT). In low-energy (i.e., 5 keV for Si, 20 keV for CdTe and CZT) threshold images, for 125 mAs acquisitions, (noise magnitudes, HU for bone insert) measured in ACR phantom were (76.0 HU, 889.4 HU), (76.9 HU, 932.9 HU), (81.7 HU, 939.4 HU)
Deep neural networks are known to be vulnerable to adversarial attacks (AA).For an image recognition task, this means that a small perturbation of the original can result in the image being *** of such attacks as well...
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Melanoma is a deadly kind of skin cancer which can spread to other parts of the body. Therefore, it is necessary to identify melanoma at the beginning level. Visual examinationat the time of medical examination of ski...
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Autonomous vehicles and Advanced Driving Assistance systems (ADAS) have the potential to radically change the way we travel. Many such of such vehicles currently rely on segmentation and object detection algorithms to...
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Automated inspection is a principal component in modern manufacturing aiming for Industry 4.0. With the fast development of digital imageprocessing and machine learning algorithms, quality control is often performed ...
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ISBN:
(数字)9781665462952
ISBN:
(纸本)9781665462952
Automated inspection is a principal component in modern manufacturing aiming for Industry 4.0. With the fast development of digital imageprocessing and machine learning algorithms, quality control is often performed by computer vision systems (CV). Following the presented topic, this paper applies the CV system for non-direct length measuring of objects moving through a conveyor. The approach involves image segmentation by a convolutional neural network and segmented object processing principles. Since high-resolution images were used, segmentation was performed in a patch manner. The algorithm also involves a custom contour analysis and the application of the least-squares method for the midline of wooden plank extraction. The proposed approach is robust to the object's non-alignment and merging factors as well as shape and wooden texture variance. The presented algorithm was tested on a custom wooden planks database gathered in a real EURO pallets production environment and confirmed to work as expected ensuring +/- 1mm length measuring accuracy and 0.97s processing timing meeting the real-time requirement of the specified system.
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