The beverage industry has been leveraging automation to enhance production efficiency. An essential advancement involves the use of AI and imageprocessing to ensure the high quality of products. imageprocessing syst...
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ISBN:
(纸本)9798331517939;9788993215380
The beverage industry has been leveraging automation to enhance production efficiency. An essential advancement involves the use of AI and imageprocessing to ensure the high quality of products. imageprocessingsystems employ sophisticated algorithms to meticulously inspect specific aspects of the production process (liquid level, lid sealing, text print). The CNN algorithm is primarily utilized to scrutinize water bottle images to verify their quality. Maintaining consistent production speed poses a challenge, underscoring the importance of examining the imageprocessing system from various perspectives. The research proposed implementing a system that oversees liquid filling quality through an imageprocessing algorithm, a camera module, and conveyor belt speed control to address. This system monitors liquid levels and bottle capping while the production line is operational. On average, the system achieves a 98.89 percent accuracy rate in detecting liquid levels and a 100 percent accuracy rate in sealing the lids. Furthermore, the conveyor speed control can adjust automatically to detect variations in product movement speed.
The increasing prevalence of mobile devices has led to significant advancements in mobile camera systems and improved image quality. Nonetheless, mobile photography still grapples with flare corruptions such as reflec...
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ISBN:
(纸本)9798350349405;9798350349399
The increasing prevalence of mobile devices has led to significant advancements in mobile camera systems and improved image quality. Nonetheless, mobile photography still grapples with flare corruptions such as reflective flare. The absence of a comprehensive real image dataset tailored for mobile phones hinders the development of effective flare mitigation techniques. To address this issue, we present a novel real image dataset specifically designed for mobile camera systems, focusing on flare removal. Capitalizing on the distinct properties of real images, this dataset serves as a solid foundation for developing advanced flare removal algorithms. The dataset comprises over 1,100 pairs of high-quality, full-resolution images for reflective flare, which generate 2,200 paired patches, ensuring broad adaptability across various imaging conditions. Experimental results demonstrate that networks trained with synthesized data struggle to cope with the complex lighting settings present in this real image dataset. Our dataset is expected to enable an array of new research in flare removal and contribute to substantial improvements in mobile image quality, benefiting mobile photographers and end-users alike.
With the continuous development of digital imageprocessingalgorithms, its application scenarios have been integrated from the simple research of a single image and a single algorithm to a multi-algorithm fusion anal...
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Computational optical imaging (COI) systems have enabled the acquisition of high-dimensional signals through optical coding elements (OCEs). OCEs encode the high-dimensional signal in one or more snapshots, which are ...
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ISBN:
(纸本)9798350349405;9798350349399
Computational optical imaging (COI) systems have enabled the acquisition of high-dimensional signals through optical coding elements (OCEs). OCEs encode the high-dimensional signal in one or more snapshots, which are subsequently decoded using computational algorithms. Currently, COI systems are optimized through an end-to-end (E2E) approach, where the OCEs are modeled as a layer of a neural network and the remaining layers perform a specific imaging task. However, the performance of COI systems optimized through E2E is limited by the physical constraints imposed by these systems. This paper proposes a knowledge distillation (KD) framework for the design of highly physically constrained COI systems. This approach employs the KD methodology, which consists of a teacher-student relationship, where a high-performance, unconstrained COI system (the teacher), guides the optimization of a physically constrained system (the student) characterized by a limited number of snapshots. We validate the proposed approach, using a binary coded apertures single pixel camera for monochromatic and multi-spectral image reconstruction. Simulation results demonstrate the superiority of the KD scheme over traditional E2E optimization for the designing of highly physically constrained COI systems.
Cloud-based data processing latency mainly depends on the transmission delay of data to the cloud and the used data processing algorithm. To minimize the transmission delay, it is important to compress the transferred...
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ISBN:
(纸本)9798350399462
Cloud-based data processing latency mainly depends on the transmission delay of data to the cloud and the used data processing algorithm. To minimize the transmission delay, it is important to compress the transferred data without reducing the quality of the data. When using data compression algorithms, it is important to validate the impact of these algorithms on the detection quality. This work evaluates the effects of image compression and transmission over wireless interfaces on state of the art neural networks. Therefore, a modern imageprocessing platform for next generation automotive processing architectures, as used in software defined vehicles, is introduced. The impacts of different image encoders as well as data transmission parameters are investigated and discussed.
Online 3D depth profiling of molten pool/keyhole during laser processing is of great importance to evaluate the metrics of the live process. The indirect methods based on visual image and thermal radiation suffer low ...
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ISBN:
(纸本)9781510670174;9781510670167
Online 3D depth profiling of molten pool/keyhole during laser processing is of great importance to evaluate the metrics of the live process. The indirect methods based on visual image and thermal radiation suffer low correlations with pool/keyhole behavior, thus the accuracy is typically low. Optical coherence tomography (OCT) shoots a light probe coaxially with the processing beam into the pool/keyhole, hence being able to provide a direct depth measurement. When it comes to profiling the depth of an area, a galvanometer is typically used to scan the area of interests. However, the pool/keyhole intrinsically flows in a highly dynamic mode, the mechanical scanned image suffers blurs and deformation, as a rolling-shutter camera suffers when imaging object is moving fast. To address this issue, a global shutter imaging method is proposed to image the pool area synchronously. A low coherent light is split into multiple fibers, which are then bundled into a core-array fiber and guided parallelly into the laser head, resulting a multiple of interfering pairs captured and imaged at the same moment. The theoretical model of this global shutter imaging method was created and analyzed in terms of the image performance and limitations. A two-core fiber global shutter imaging system was built to demonstrate the imaging performance on molten pool/keyhole. It shows a great potential to capture high quality 3D points of keyhole/molten pool for further fine closed loop control.
This paper presents a real-time embedded thermal imaging system architecture for compact, energy-efficient, high-quality imaging utilizing heterogeneous system-on-chip (SoC) and uncooled infrared focal plane arrays (I...
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ISBN:
(纸本)9798350387964;9798350387957
This paper presents a real-time embedded thermal imaging system architecture for compact, energy-efficient, high-quality imaging utilizing heterogeneous system-on-chip (SoC) and uncooled infrared focal plane arrays (IRFPAs). Unlike previous systems that organized separate devices for complex imageprocessing, our system provides integrated imageprocessing support for robust sensor-to-surveillance. The imageprocessing organizes two algorithm stacks: a non-uniformity correction stack to mitigate the distinctive noise vulnerabilities of uncooled IRFPAs, and an image enhancement stack including contrast enhancement and temporal noise filters. We optimized these algorithms for domain-specific factors, including asymmetric multiprocessing (AMP), cache organization, single instruction multiple data (SIMD) instructions, and very long instruction word (VLIW) architectures. The implementation on the TI TDA3x SoC demonstrates that our system can process 640x480, 60 frames per second (FPS) videos at a peak core load of 57.5% while consuming power less than 2.2 W for the entire system, denoting the possibility of processing the 1280x1024, 30 FPS videos from the cutting-edge uncooled IRFPAs. Additionally, our system improves power efficiency by 9.42% and 9.96% at 30 and 60 FPS, respectively, compared to the state-of-the-art when executing similar imageprocessingalgorithms.
This study introduces a machine vision system integrated into cyber-physical systems (CPS) for enhanced industrial control. The system employs a specialized script for real-time imageprocessing and edge detection, wi...
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ISBN:
(纸本)9798350372977;9798350372984
This study introduces a machine vision system integrated into cyber-physical systems (CPS) for enhanced industrial control. The system employs a specialized script for real-time imageprocessing and edge detection, with a focus on precision and speed. Results showcase the system's rapid processing capabilities and high-accuracy feature detection, facilitated by machine learning algorithms that enable adaptability and iterative improvement. The system distinguishes itself by not only providing rapid and accurate feature recognition but also by outputting precise coordinates, crucial for micron-level manufacturing precision. An intuitive human-machine interface ensures seamless operation within industrial workflows. This integration significantly improves automated quality control and operational efficiency, demonstrating the system's potential to advance smart manufacturing in line with Industry 4.0 standards.
Superpixel-based segmentation is an important preprocessing step for the simplification of imageprocessing. The subjective nature behind the determination of optimal cluster numbers in segmentation algorithms can res...
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ISBN:
(纸本)9798350366235;9798350366242
Superpixel-based segmentation is an important preprocessing step for the simplification of imageprocessing. The subjective nature behind the determination of optimal cluster numbers in segmentation algorithms can result in either under-or over-segmentation burdens, depending on the image type. Insect wings, with their intricate color patterns, pose significant challenges for the accurate capture of color diversity in clustering algorithms, assuming a spherical and isotropic cluster distribution is used. This paper introduces a hybrid approach for color clustering in insect wings, integrating the Simple Linear Iterative Clustering (SLIC) method to generate the initial superpixels, and a DeltaE 2000 function the precisely discriminated merging of superpixels. Color differences between superpixels serve to measure homogeneity during the merging process. The proposed new algorithm demonstrates enhanced segmentation as it overcomes the issue of over-segmentation and under-segmentation, as evidenced by the results derived from the Boundary Recall, Rand index, Under-segmentation Error, and Bhattacharyya distance using ground truth data. The Silhouette score and Dunn Index are also used to quantitatively evaluate the efficacy of our new proposed clustering technique.
At present, the application of industrial robots combined with visual systems to achieve dynamic grasping materials of the belt is becoming increasingly widespread. Unlike the behavior of industrial robots grabbing af...
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At present, the application of industrial robots combined with visual systems to achieve dynamic grasping materials of the belt is becoming increasingly widespread. Unlike the behavior of industrial robots grabbing after the belt stops, industrial robots dynamically tracking and grabbing materials on the belt can greatly improve production efficiency. For vision, processing distorted material images during high-speed movement and to obtain accurate coordinate points of materials is a key task to improve the accuracy of the belt tracking applications with industrial robot. Developing imageprocessingalgorithms based on MATLAB can, on the one hand, utilize existing software and hardware interface functions to improve development efficiency;On the other hand, autonomous and controllable imageprocessingalgorithms can be developed based on application requirements to maximize system accuracy.
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