- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2018 10th International Conference on Modelling, Identification and Control (ICMIC) - Guiyang, China (2018.7.2-2018.7.4)] 2018 10th International Conference on Modelling, Identification and Control (ICMIC) - Automatic Reading System for Analog Instruments Based on Computer Vision and Inspection Robot for Power Plant
摘要： In this paper, an automatic reading system for analog instruments has been designed for monitoring in power plants. In a general automatic reading system, there are many limitations to the reading correctness and system robustness such as the high cost for the reason that there is only one instrument could be monitored by a single system, the strict restrict of the camera angle, and being not suitable for instruments with dense scales and so on. We present some solutions to overcome these limitations. Firstly, we combine a mobile inspection robot with an image capture device and the image processing method to cut the cost of the monitoring of analog instruments in power plants. Then, we use Hough transform and perspective transform to correct the geometric distortion of images caused by camera angle. Eventually, we get the result of dense scaled instruments based on polar transform. Experiments show that our system performs quite well, and the reading error is less than the results which obtained from the general automatic reading system.
关键词： Computer vision,Analog instruments,Automatic reading,Routing inspection robot
更新于2025-09-10 09:29:36
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[IEEE 2018 IEEE International Conference "Quality Management, Transport and Information Security, Information Technologies" (IT&QM&IS) - Saint Petersburg, Russia (2018.9.24-2018.9.28)] 2018 IEEE International Conference "Quality Management, Transport and Information Security, Information Technologies" (IT&QM&IS) - Algorithms for Detecting Potato Defects Using Images in the Infrared Range of Spectrum
摘要： An automated system for contactless thermal quality testing of potato moving along a chain conveyor is presented. The algorithm of the computer vision system for the recognition of potato defects in real time is described. The method for detecting defects is based on determining the temperature difference between healthy and damaged tissues after short-term heating of the tubers.
关键词： noncontact,computer vision,nondestructive,potato,testing,defect,infrared
更新于2025-09-10 09:29:36
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[IEEE 2018 10th International Conference on Modelling, Identification and Control (ICMIC) - Guiyang, China (2018.7.2-2018.7.4)] 2018 10th International Conference on Modelling, Identification and Control (ICMIC) - Research on Multiple Features Extraction Technology of Insulator Images
摘要： The insulators are important components of high voltage transmission line. They affect the safety of electric power system. Computer Vision is proposed to extract the kinds of characteristic values of insulator images. These values can provide information for insulator detection and recognition, and then protect the power system safely. The actual insulators are segmented firstly by use of pixel statistical method. The textural features are extracted by use of Gray level cooccurrence matrix. The invariant moment features are extracted in the binary image. The geometric features are computed by local property and pick up the boundary contour. Finally, local features are used for detecting insulator features.
关键词： Computer vision,Insulator,Invariant moment,Local features,Feature extraction,Texture
更新于2025-09-10 09:29:36
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Nanoscale measurement with pattern recognition of an ultra-precision diamond machined polar microstructure
摘要： Due to the low resolution of pattern recognition and disorganized textures of the surfaces of most natural objects observed under a microscope, computer vision technology has not been widely applied in precision positioning measurement on machine tools, which needs high resolution and accuracy. This paper presents a systematic method to solve the surface recognition problem which makes use of ultra-precision diamond machining to produce a functional and polar-coordinate surface named ‘polar microstructure’. The unique characteristic of a polar microstructure is the distinctive pattern of any locations including rotation in the global surface which provides the feasibility of achieving precise absolute positions by matching the patterns by utilizing computer vision technology. A polar microstructure which possesses orientation characteristics is also able to measure the displacement of rotation angle. A series of simulation experiments including feature point extraction, orientation detection as well as resolution of pattern recognition was conducted, and the results show that a polar microstructure can achieve a resolution of 9.35 nm which is capable of providing a novel computer vision-based nanometric precision measurement method which can be applied in positioning on machine tools in the future.
关键词： Ultra-precision machining,Polar microstructure,Nanoscale measurement,Computer vision,Pattern recognition
更新于2025-09-10 09:29:36
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Image Quality Assessment and Outliers Filtering in an Image-Based Animal Supervision System
摘要： This paper presents a probabilistic framework for the image quality assessment (QA), and filtering of outliers, in an image-based animal supervision system (asup). The proposed framework recognizes asup’s imperfect frames in two stages. The first stage deals with the similarity analysis of the same-class distributions. The objective of this stage is to maximize the separability measures by defining a set of similarity indicators (SI) under the condition that the number of permissible values for them is restricted to be relatively low. The second stage, namely faulty frame recognition (FFR), deals with asup’s QA training and real-time quality assessment (RTQS). In RTQS, decisions are made based on a real-time quality assessment mechanism such that the majority of the defected frames are removed from the consecutive sub routines that calculate the movements. The underlying approach consists of a set of SI indexes employed in a simple Bayesian inference model. The results confirm that a significant amount of defected frames can be efficiently classified by this approach. The performance of the proposed technique is demonstrated by the classification on a cross-validation set of mixed high and low quality frames. The classification shows a true positive rate of 88.6% while the false negative rate is only about 2.5%.
关键词： Quality Assessment,Naive Bayes,Computer Vision,Graphical Model,Agriculture
更新于2025-09-10 09:29:36
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[IEEE 2018 International Conference On Advances in Communication and Computing Technology (ICACCT) - Sangamner, India (2018.2.8-2018.2.9)] 2018 International Conference On Advances in Communication and Computing Technology (ICACCT) - Traffic Sign Detection for Advanced Driver Assistance System
摘要： Development of safety features so as to prevent ignorance of traffic sign boards mounted on road is one of the major technical challenges in the automobile industry. Ignoring traffic signs can lead to major road accidents. Therefore, using driver assistance system to timely assist with warning and information road signs can be of significant help in prevention of accidents. This paper aims towards the detection of road signs using contour analysis approach. In this paper Blue, Green, Red (BGR) to Hue, Saturation, Value (HSV) conversion model and morphological filter for noise filtering are used to make the result more robust. The system has a voice trigger to alert the driver of road signs via audio message and thus helping in prevention of accidents.
关键词： computer vision,traffic sign detection,driver safety,contour detection,advanced driver assistance
更新于2025-09-10 09:29:36
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[IEEE 2018 International Conference on 3D Vision (3DV) - Verona (2018.9.5-2018.9.8)] 2018 International Conference on 3D Vision (3DV) - Four- and Seven-Point Relative Camera Pose from Oriented Features
摘要： Determining relative camera pose is a fundamental problem in computer vision, and pose is often computed from feature correspondences. For point features, a minimum of five correspondences are required to determine the pose between two calibrated cameras, and eight corresponding points can be used to form a linear solution. However, most feature detectors used in practice produce points with an associated orientation. This work demonstrates that with oriented features the relative pose of two cameras can be computed from just four point correspondences, or seven with a linear solution. These new four- and seven-point algorithms do not require any additional sensors or parameters, but exploit information (feature orientation) that is already computed by most existing structure-from-motion systems. On the DTU multi-view stereo data set the four-point algorithm is shown to be 55% faster than the five-point algorithm, and the seven-point linear algorithm gives a 43% speed improvement over the eight-point algorithm.
关键词： computer vision,oriented features,essential matrix,RANSAC,relative camera pose
更新于2025-09-10 09:29:36
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Reflecting health: smart mirrors for personalized medicine
摘要： Inexpensive embedded computing and the related Internet of Things technologies enable the recent development of smart products that can respond to human needs and improve everyday tasks in an attempt to make traditional environments more “intelligent”. Several projects have augmented mirrors for a range of smarter applications in automobiles and homes. The opportunity to apply smart mirror technology to healthcare to predict and to monitor aspects of health and disease is a natural but mostly underdeveloped idea. We envision that smart mirrors comprising a combination of intelligent hardware and software could identify subtle, yet clinically relevant changes in physique and appearance. Similarly, a smart mirror could record and evaluate body position and motion to identify posture and movement issues, as well as offer feedback for corrective actions. Successful development and implementation of smart mirrors for healthcare applications will require overcoming new challenges in engineering, machine learning, computer vision, and biomedical research. This paper examines the potential uses of smart mirrors in healthcare and explores how this technology might bene?t users in various medical environments. We also provide a brief description of the state-of-the-art, including a functional prototype concept developed by our group, and highlight the directions to make this device more mainstream in health-related applications.
关键词： machine learning,Internet of Things,computer vision,healthcare,smart mirrors,personalized medicine
更新于2025-09-10 09:29:36
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Automated leaf disease detection in different crop species through image features analysis and One Class Classifiers
摘要： The presented approach demonstrates an automated way of crop disease identification on various leaf sample images corresponding to different crop species employing Local Binary Patterns (LBPs) for feature extraction and One Class Classification for classification. The proposed methodology uses a dedicated One Class Classifier for each plant health condition including, healthy, downy mildew, powdery mildew and black rot. The algorithms trained on vine leaves have been tested in a variety of crops achieving a very high generalization behavior when tested in other crops. An original algorithm proposing conflict resolution between One Class Classifiers provides the correct identification when ambivalent data examples possibly belong to one or more conditions. A total success rate of 95% is achieved for the total for the 46 plant-condition combinations tested.
关键词： Computer vision,Machine learning,Local descriptors,Crop health status,Precision agriculture
更新于2025-09-09 09:28:46
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[ASME ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference - Quebec City, Quebec, Canada (Sunday 26 August 2018)] Volume 1A: 38th Computers and Information in Engineering Conference - Multi-Resolution-Based Contour Corner Extraction Algorithm for Computer Vision-Based Measurement
摘要： Corner-based registration of the industry standard contour and the actual product contour is one of the key steps in industrial computer vision-based measurement. However, existing corner extraction algorithms do not achieve satisfactory results in the extraction of the standard contour and the deformed contour of the actual product. This paper proposes a multi-resolution-based contour corner extraction algorithm for computer vision-based measurement. The algorithm first obtains different corners in multiple resolutions, then sums up the weighted corner values, and finally chooses the corner points with the appropriate corner values as the final contour corners. The experimental results show that the proposed algorithm, based on multi-resolution, outperforms the original algorithm in the aspect of the corner subsequent product matching measurements.
关键词： contour corner extraction,multi-resolution,computer vision-based measurement,corner pairing rate
更新于2025-09-09 09:28:46