Near-infrared (NIR) band sensors capture achromatic images that contain complementary details of a scene which are diminished in visible (VS) band images when the scene is obscured by haze, mist, or fog. To exploit th...
详细信息
Near-infrared (NIR) band sensors capture achromatic images that contain complementary details of a scene which are diminished in visible (VS) band images when the scene is obscured by haze, mist, or fog. To exploit these complementary details, an integrated FPGA architecture and implementation of a videoprocessing system are proposed in this paper. This system performs VS-NIR video fusion and produces an enhanced VS video in real-time. The proposed FPGA architecture and implementation effectively handle the challenges associated with the simultaneous processing of video signals obtained from different sources such as the inevitable delay among corresponding frames and time-varying deviation among frame rates. Moreover, the proposed implementation is efficiently designed and able to produce the fused video at the same frame rate as the input videos, i.e. in real-time, regardless of the resolution of the input videos while the consumed FPGA resources are kept small. This is achieved by data and calculations reuse, besides performing operations concurrently in parallel and pipelined fashions at both the data and task levels. The proposed implementation is synthesized, validated on a low-end FPGA device, and compared to three other implementations. The comparison shows the superiority of the proposed implementation in terms of the consumed resources which have a direct industrial impact in the case of integration in modern smart-phones and cameras.
Fire detection of surveillance video in laboratory management is an important security work. In this paper, a fire detection method based on deep learning and motion features is proposed to improve the accuracy and re...
详细信息
Conventional vehicle counting using various techniques such as manual counts are no longer efficient in the era of industrial revolution 4.0. The algorithm within the intelligence system using a realtimevideo and im...
详细信息
ISBN:
(纸本)9781510691704
Conventional vehicle counting using various techniques such as manual counts are no longer efficient in the era of industrial revolution 4.0. The algorithm within the intelligence system using a realtimevideo and imageprocessing technique is proposed due to its reliability, efficiency, cost effectiveness and safety for gathering data. Surveillance cameras commonly installed in large cities could be used to obtain traffic data recording, allowing for an automated system to be easily adopted at minimal cost. This study provides an alternative and economical means to estimate traffic density via video-imageprocessing which adopts OpenCV in the Python code. This method only requires a fixed video camera be positioned at an elevated position such as on a pedestrian bridge or a light pole. The images are processed automatically through OpenCV code bindings in Python. The system requires frames from the video to be captured so background subtraction can be performed to detect and count the vehicles using Gaussian Mixture Model. The classification of vehicles by size is done by comparing the contour areas to the assumed values. The proposed algorithm can be adapted to meet the requirements of the user and the camera’s position. The algorithm allows traffic data to be obtained, which may assist local authorities make decisions regarding urban planning and the design of transportation systems. Sample videos of traffic scenes were used to compare the detection and classification of vehicles. Results from the proposed algorithm were compared with manual count results from the field. Analysis of the classification and volume count of vehicles using the proposed algorithm is shown to have an error rate of 1.3% compared to an error rate of 6.4% using the manual tally counter method. The results confirmed that the proposed automatic counting system performed better when compared to the manual tally counter method with the additional benefits of increase cost efficiency and impr
Deep learning has revolutionized high-level imageprocessing tasks, notably image classification and segmentation, by effectively handling multi-dimensional features in image space. This report investigates the applic...
详细信息
Smoothness assessment plays a key role in evaluating the quality of asphalt concrete pavements, which has a direct impact on vehicle comfort, safety, and pavement longevity. This study presents a novel approach to asp...
详细信息
The indoor imaging visible light positioning (VLP) technology based on the image sensor (IS) utilizes existing indoor lighting infrastructure to provide high-precision indoor positioning services. However, due to the ...
详细信息
In order to solve the problem of fire detection in the heat exchange station, an intelligent fire early warning system based on image analysis is proposed, which realizes the network, digital and intelligent design of...
详细信息
Background: Ship detection in video surveillance images holds significant practical value. However, the background in these images is often complex, complicating the achievement of an optimal balance between detection...
详细信息
Background: Ship detection in video surveillance images holds significant practical value. However, the background in these images is often complex, complicating the achievement of an optimal balance between detection precision and speed. Method: This study proposes a ship detection method that leverages semantic aggregation in complex backgrounds. Initially, a semantic aggregation module merges deep features, rich in semantic information, with shallow features abundant in location details, extracted via the front-end network. Concurrently, these shallow features are reshaped through the reorg layer to extract richer feature information, and then these reshaped shallow features are integrated with deep features within the feature fusion module, thereby enhancing the capability for feature fusion and improving classification and positioning capability. Subsequently, a multiscale object detection layer is implemented to enhance feature expression and effectively identify ship objects across various scales. Moreover, the distance intersection over union (DIoU) metric is utilized to refine the loss function, enhancing the detection precision for ship objects. Results: The experimental results on the SeaShips dataset and SeaShips_enlarge dataset demonstrate that the mean average precision@0.5 (mAP@0.5) of this proposed method reaches 89.30% and 89.10%, respectively. Conclusions: The proposed method surpasses other existing ship detection techniques in terms of detection effect and meets real-time detection requirements, underscoring its engineering relevance.
Diffusion models have achieved remarkable success in generating high quality image and video data. More recently, they have also been used for image compression with high perceptual quality. In this paper, we present ...
详细信息
In recent years, with the development of digital technology, digital imageprocessing has been widely and deeply applied in the field of computer graphics. Digital imageprocessing system is a complex real-time system...
详细信息
ISBN:
(纸本)9781665487894
In recent years, with the development of digital technology, digital imageprocessing has been widely and deeply applied in the field of computer graphics. Digital imageprocessing system is a complex real-time system, it from the camera, fax machine and other scanning equipment to obtain image information, after digital transformation, digital image information coding, filtering, enhancement, recovery, compression, storage and other processing, finally generate visual image. This design uses TMS320C6748 as the core processor of the system, SAA7113 as the video decoding chip of the system, CPLD as the sampling controller, DDR2 chip as the external expansion memory. The ROM expansion uses NAND flash memory chip. On the basis of hardware design, combined with software algorithm to complete imageprocessing. The system can be used in information communication, image recognition, news scene and other fields of imageprocessing and transmission. This paper analyzes the hardware structure and data processing algorithm of the system in detail. The experimental results show that the system can not only obtain higher compression ratio, but also reduce the distortion of the reconstructed image. The imageprocessing system has certain practicability.
暂无评论