Due to image reconstruction process of all image capturing methods, image data is inherently affected by uncertainty. This is caused by the underlying image reconstruction model, that is not capable to map all physical properties in its entirety. In...
Even though computer vision has been developing, edge detection is still one of the challenges in that field. It comes from the limitations of the complementary metal oxide semiconductor (CMOS) Image sensor used to collect the image data, and then im...
Infrared imaging sensors are frequently used in thermal signature detection applications in industrial, automotive, military and many other areas. However, advanced infrared detectors are generally associated with high costs and complexity. Infrared...
Currently, there is a demand for an increase in the diversity and quality of new products reaching the consumer market. This fact imposes new challenges for different industrial sectors, including processes that integrate machine vision. Hardware acc...
Image pre-processing is crucial for large fleet management. Many traffic videos are collected by closed-circuit television (CCTV), which has a fixed area monitoring for image analysis. This paper adopts the front camera installed in large vehicles to...
JPEG is the international standard for still image encoding and is the most widely used compression algorithm because of its simple encoding process and low computational complexity. Recently, many methods have been developed to improve the quality o...
In applications such as environmental monitoring, algorithms and deep learning-based methods using synthetic aperture radar (SAR) and electro-optical (EO) data have been proposed with promising results. These results have been achieved using already...
Background: Recent studies have shown that hyperspectral imaging (HSI) combined with neural networks can detect colorectal cancer. Usually, different pre-processing techniques (e.g., wavelength selection and scaling, smoothing, denoising) are analyze...
In computed tomography imaging, the computationally intensive tasks are the pre-processing of 2D detector data to generate total attenuation or line integral projections and the reconstruction of the 3D volume from the projections. This paper propose...
Thermal imaging plays a vital role in structural health monitoring of various materials and provides insight into the defect present due to aging, deterioration, and fault during construction. This study investigated the effectiveness of spatial filt...
This research provides a practical guideline for Digital Image Correlation (DIC) data variations minimization in structural engineering through simple image processing techniques. The main objective of this research is to investigate the Pixel Averag...
Small target features are difficult to distinguish and identify in an environment with complex backgrounds. The identification and extraction of multi-dimensional features have been realized due to the rapid development of deep learning, but there ar...
Uncrewed-Aerial Vehicles (UAVs) and hyperspectral sensors are emerging as effective alternatives for monitoring water quality on-demand. However, image mosaicking for largely featureless coastal water surfaces or open seas has shown to be challenging...
Mammography is the most preferred method for breast cancer screening. In this study, computer-aided diagnosis (CAD) systems were used to improve the image quality of mammography images and to detect suspicious areas. The main contribution of this stu...
Radiomics of pancreas magnetic resonance (MR) images is positioned well to play an important role in the management of diseases characterized by diffuse involvement of the pancreas. The effect of image pre-processing configurations on these images ha...
MRI perfusion is used to diagnose and monitor neurological conditions such as brain tumors, stroke, dementia, and traumatic brain injury. Dynamic Susceptibility Contrast (DSC) is the most widely available quantitative MRI technique for perfusion imag...
In the present investigation, we have devised a hyperspectral imaging (HSI) apparatus to assess the chemical characteristics and freshness of the yellow croaker (Larimichthys polyactis) throughout its storage period. This system operates within the s...
Unmanned aerial vehicle (UAV) imaging is a promising data acquisition technique for image-based plant phenotyping. However, UAV images have a lower spatial resolution than similarly equipped in field ground-based vehicle systems, such as carts, becau...
In recent years, lung cancer prediction is an essential topic for reducing the death rate of humans. In the literature section, some papers are reviewed that reduce the accuracy level during the prediction stage. Hence, in this paper, we develop a Mu...
Thermal cameras, as opposed to RBG cameras, work effectively in extremely low illumination situations and can record data outside of the human visual spectrum. For surveillance and security applications, thermal images have several benefits. However,...
For the problem of classification and identification of defects in polyethylene (PE) gas pipelines, this paper firstly performs preliminary screening of the acquired images and acquisition efficiency of defective image acquisition was improved. Image...
Automated image-based 3D reconstruction methods are more and more flooding our 3D modeling applications. Fully automated solutions give the impression that from a sample of randomly acquired images we can derive quite impressive visual 3D models. Alt...
Imaging biomarkers require technical, biological, and clinical validation to be translated into robust tools in research or clinical settings. This study contributes to the technical validation of radiomic features from magnetic resonance imaging (MR...
This study presents a development plan for a vision AI system to enhance productivity in industrial environments, where environmental control is challenging, by using AI technology. An image pre-processing algorithm was developed using a mobile robot...
Breast cancer is now the most frequently diagnosed cancer in women, and its percentage is gradually increasing. Optimistically, there is a good chance of recovery from breast cancer if identified and treated at an early stage. Therefore, several rese...
Content-Based Histopathological Image Retrieval (CBHIR) is a search technique based on the visual content and histopathological features of whole-slide images (WSIs). CBHIR tools assist pathologists to obtain a faster and more accurate cancer diagnos...
Land-use and land-cover (LULC) classification using remote sensing imagery plays a vital role in many environment modeling and land-use inventories. In this study, a hybrid feature optimization algorithm along with a deep learning classifier is propo...
The system that automatically identifies the anthropometric fingerprint is one of the systems that interact directly with the user, which every day will be provided with a diverse database. This requires the system to be optimized to handle the proce...
Optical Character Recognition has made large strides in the field of recognizing printed and properly formatted text. However, the effort attributed to developing systems that are able to reliably apply OCR to both printed as well as handwritten text...
The future exploration plans of the industry is to find a small-scale reservoir for possible economic hydrocarbon reserves. These reserves could be illuminated by the super-resolution of full seismic data, including fractured zones, pinch-outs, chann...
Diabetic retinopathy (DR) is the foremost cause of blindness in people with diabetes worldwide, and early diagnosis is essential for effective treatment. Unfortunately, the present DR screening method requires the skill of ophthalmologists and is tim...
Timely identification and accurate delineation of ultra-early ischemic stroke lesions in non-contrast computed tomography (CT) scans of the human brain are of paramount importance for prompt medical intervention and improved patient outcomes. In this...
Lung diseases are the third-leading cause of mortality in the world. Due to compromised lung function, respiratory difficulties, and physiological complications, lung disease brought on by toxic substances, pollution, infections, or smoking results i...
Epicutaneous patch testing is a well-established diagnostic method for identifying substances that may cause Allergic Contact Dermatitis (ACD), a common skin condition caused by exposure to environmental allergens. While the patch test remains the go...
The investigation of plant phenotypes through 3D modeling has emerged as a significant field in the study of automated plant phenotype acquisition. In 3D model construction, conventional image preprocessing methods exhibit low efficiency and inherent...
Early detection of smoke having indistinguishable pixel intensities in digital images is a difficult task. To better maintain fire surveillance, early smoke detection is crucial. To solve the problem, we have integrated the principal component analys...
Tree species information is important for forest management, especially in seedling stands. To mitigate the spectral admixture of understory reflectance with small and lesser foliaged seedling canopies, we proposed an image pre-processing step based...
This review analyzes recent advancements in facial recognition and classification algorithms, emphasizing the critical role of preprocessing techniques in enhancing the algorithms’ accuracy, reliability, and efficiency. Facial image preprocessi...
Edge Computing enables to perform measurement and cognitive decisions outside a central server by performing data storage, manipulation, and processing on the Internet of Things (IoT) node. Also, Artificial Intelligence (AI) and Machine Learning appl...
Long-range airborne streak tube imaging lidar (ASTIL) raw echo images are degraded by atmospheric speckle, detector noise, and weak-return fluctuations, which can bias centroid localization before range calculation. This study presents a lightweight...
The automatic identification of plant species using unmanned aerial vehicles (UAVs) is a valuable tool for ecological research. However, challenges such as reduced spatial resolution due to high-altitude operations, image degradation from camera opti...
Accurate and interpretable brain tumour detection from magnetic resonance imaging (MRI) is important for the reliable use of computer-assisted diagnostic systems. This study examines whether image preprocessing can improve the localisation quality of...
Early diagnosis of cancer is very important as it significantly increases the chances of appropriate treatment and survival. To this end, Deep Learning models are increasingly used in the classification and segmentation of histopathological images, a...
Ship wake detection using synthetic aperture radar (SAR) imagery provides a way to obtain small marine ship information, but it often becomes unavailable and unreliable during a high sea state. Polarimetric information provides a potential way to sol...
The satellite image time series are used for several applications such as predictive analysis. New techniques such as deep learning (DL) algorithms generally require long sequences of data to perform well; however, the complexity of satellite image p...
Skin cancer is a widespread and fatal disease in which early and accurate detection is an important aspect for effective treatment. The issues that arise when performing automated analysis of dermatoscopic images include artifacts such as hair, low c...
This work presents a novel approach to enhancing iris recognition systems through a two-module approach focusing on low-level image preprocessing techniques and advanced feature extraction. The primary contributions of this paper include: (i) the dev...
This study addresses the critical challenge of variable image quality in deep learning-based automated pest identification. We propose a holistic pipeline that integrates systematic Image Quality Assessment (IQA) with tailored preprocessing to enhanc...
Since remote sensing images are one of the main sources for people to obtain required information, the quality of the image becomes particularly important. Nevertheless, noise often inevitably exists in the image, and the targets are usually blurred...
Ethnicity recognition has become increasingly important for a wide range of applications, highlighting the need for accurate and robust predictive models. Despite advances in machine learning, ethnicity classification remains a challenging research p...
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