Accurate vehicle detection plays a vital role in intelligent transportation systems. Various day conditions, for instance, dawn, morning, noon, or non-uniform illuminations put restrictions on camera's visibility....
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Accurate vehicle detection plays a vital role in intelligent transportation systems. Various day conditions, for instance, dawn, morning, noon, or non-uniform illuminations put restrictions on camera's visibility. Such scenarios impact the performance of detection and recognition algorithms that are used in surveillance systems and autonomous driving. This paper aims to solve the aforementioned issues using machine learning methods, such as face detection and recognition. The core theme of this paper is the development of a vehicle detection and driver recognition system, which also focuses the situation where an input image is degraded by non-uniform illuminations. The proposed system is composed of four main processing modules: (i) image acquisition, (ii) image enhancement, (iii) object detection that locates vehicles' and drivers' faces, and (iv) the Pool of Face Recognition algorithms (PoFRA), which uses four face recognition algorithms to conclude the driver's identity. We implement suitable algorithms for each of the above-described modules to appraise its practicability. The system can be adjusted to work in different types of extreme weather conditions, such as strong or dim light. Experimental results demonstrate that the proposed system has significant potential to take the research on automated car parking systems to the next level.
Matrix methods for constructing order-16 integer sine and cosine transforms of type iv (IST-iv/ICT-iv) are proposed. Based on the method two integer sine and cosine transforms of type iv are constructed and fast algor...
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ISBN:
(纸本)9781510679344;9781510679351
Matrix methods for constructing order-16 integer sine and cosine transforms of type iv (IST-iv/ICT-iv) are proposed. Based on the method two integer sine and cosine transforms of type iv are constructed and fast algorithms for computing of these transforms are developed, which require only integer operations. These algorithms have low multiplicative complexity, being 4.9 times less, and require 127,37% more addition operations compared to the well-known algorithms of discrete sine and cosine transforms type iv. The proposed fast IST-iv/ICT-iv, compared to the well-known fast DST-VII/DCT-VIII in the VVC standard, have multiplicative complexity that is 12.7 times less and require 26.32% more addition operations.
This research studied the effect of variations in a sensor's F lambda/d metric value (FLD) on the performance of machine learning algorithms such as the YOLO (You Only Look Once) algorithm for object classificatio...
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This research studied the effect of variations in a sensor's F lambda/d metric value (FLD) on the performance of machine learning algorithms such as the YOLO (You Only Look Once) algorithm for object classification. The YOLO_v3 and YOLO_v10 algorithms were trained using static imagery provided in the commonly available training dataset provided by Teledyne FLIR systems. imageprocessing techniques were used to degrade image quality of the test dataset also provided by Teledyne FLIR systems, simulating detector-limited to optics-limited performance, which results in a variation of the FLD metric between 0.339 and 7.98. The degraded test set was used to evaluate the performance of YOLO_v3 and YOLO_v10 for object classification and relate the FLD metric to the probability of detection. Results of YOLO_v3 and YOLO_v10 are presented for the varying levels of image degradation. A summary of the results is discussed along with recommendations for evaluating an algorithm's performance using a sensor's FLD metric value. (c) 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.
This article presents a new image segmentation algorithm based on a Split & Merge approach. By nature, the execution time of Split & Merge algorithms is data-dependent, as their halting conditions are tied to ...
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ISBN:
(纸本)9798350349405;9798350349399
This article presents a new image segmentation algorithm based on a Split & Merge approach. By nature, the execution time of Split & Merge algorithms is data-dependent, as their halting conditions are tied to the homogeneity of each region. While previous algorithms made the Split step less sensitive to input data, the execution time of the more complex Merge step remains highly sensitive to image content. This paper tackles the sensitivity and performance problems from a system and architecture perspective. Memory reallocations due to array fusions are eliminated with the introduction of a TTA (Three Table Array) structure in the Merge step. As iterating over entries in this structure causes a loss of memory locality, we propose two new mechanisms that implement a software cache to mitigate this. An experimental study on an embedded system (Nvidia Jetson Xavier NX) has shown our Merge algorithm to be 10.6 times faster than the state-of-the-art Split & Merge algorithm for 960 x 720 images. Moreover, the execution time of our algorithm is also more resistant to image characteristics.
The development of biomedical image technology has brought significant advancements to healthcare and frontier research. Over the past 20 years, BioCAS has witnessed and documented comprehensive achievements in biomed...
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ISBN:
(纸本)9798350354966;9798350354959
The development of biomedical image technology has brought significant advancements to healthcare and frontier research. Over the past 20 years, BioCAS has witnessed and documented comprehensive achievements in biomedical image sensor design and processingalgorithms. This paper provides a systematic review of the work related to biomedical image acquisition and processing technology in BioCAS and offers a perspective on future developments in this field.
With the rapid development of deep learning technology, its application in imageprocessing and recognition has become a hot research topic. The application of these technologies in software information systems such a...
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This paper explores the utilization of MATLAB for digital signal processing (DSP) techniques in imageprocessing tasks, focusing on image deblurring, face detection, and facial feature enhancement. Blind deconvolution...
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ISBN:
(纸本)9798350372113;9798350372106
This paper explores the utilization of MATLAB for digital signal processing (DSP) techniques in imageprocessing tasks, focusing on image deblurring, face detection, and facial feature enhancement. Blind deconvolution methods are employed to address image blurriness, while face detection is facilitated using cascaded object detectors. Enhancements to detected facial features involve histogram equalization, smoothing filters, skin tone adjustment, and contrast enhancement techniques, followed by seamless integration using resizing methods. MATLAB serves as a robust platform for implementing and analyzing DSP algorithms, providing insights into practical solutions for common challenges in digital imageprocessing.
This research paper explores the application of singular value decomposition (SVD) in quantum imageprocessing (QIP), specifically focusing on the computation of eigenvalues using variational quantum algorithms. SVD i...
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The quality of image signals directly affects the performance of intelligent communication systems. This paper proposes a set of image enhancement and denoising algorithms to address image quality degradation in intel...
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This paper presents ternary systolic array architecture for matrix multiplication for ternary neural networks and imageprocessingalgorithms in ternary logic. As part of the architecture, we have proposed a processin...
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ISBN:
(纸本)9798350381191
This paper presents ternary systolic array architecture for matrix multiplication for ternary neural networks and imageprocessingalgorithms in ternary logic. As part of the architecture, we have proposed a processing element of a systolic array architecture. The processing element is designed using a partial product calculator, which does the multiply-accumulate operation using single-digit multipliers and adders. All proposed circuits are designed in CNFET-Memristor technology and simulated using Cadence Virtuoso. The propagation delay, power, and power delay product of the proposed circuits are calculated using simulations. The proposed matrix multiplication is used in the Gaussian smoothing of images and results were presented.
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