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Wyszukujesz frazę "image detection" wg kryterium: Temat


Tytuł:
Histogram of Oriented Gradients with Cell Average Brightness for Human Detection
Autorzy:
Wójcikowski, M.
Powiązania:
https://bibliotekanauki.pl/articles/221424.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
digital image processing
object detection
human detection
Opis:
A modification of the descriptor in a human detector using Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM) is presented. The proposed modification requires inserting the values of average cell brightness resulting in the increase of the descriptor length from 3780 to 3908 values, but it is easy to compute and instantly gives ≈ 25% improvement of the miss rate at 10‒4 False Positives Per Window (FPPW). The modification has been tested on two versions of HOG-based descriptors: the classic Dalal-Triggs and the modified one, where, instead of spatial Gaussian masks for blocks, an additional central cell has been used. The proposed modification is suitable for hardware implementations of HOG-based detectors, enabling an increase of the detection accuracy or resignation from the use of some hardware-unfriendly operations, such as a spatial Gaussian mask. The results of testing its influence on the brightness changes of test images are also presented. The descriptor may be used in sensor networks equipped with hardware acceleration of image processing to detect humans in the images.
Źródło:
Metrology and Measurement Systems; 2016, 23, 1; 27-36
0860-8229
Pojawia się w:
Metrology and Measurement Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Survey on Facial Features Detection
Autorzy:
Naruniec, J.
Powiązania:
https://bibliotekanauki.pl/articles/226792.pdf
Data publikacji:
2010
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
object detection
image processing
face recognition
Opis:
In this article chosen approaches to the facial features detection have been gathered and described. In the conclusion author discusses advantages and disadvantages of the presented algorithms.
Źródło:
International Journal of Electronics and Telecommunications; 2010, 56, 3; 267-272
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
LEDs based video camera pose estimation
Autorzy:
Sudars, K.
Cacurs, R.
Homjakovs, I.
Judvaitis, J.
Powiązania:
https://bibliotekanauki.pl/articles/200249.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
camera pose estimation
image keypoint detection and matching
3D point reconstruction
object localization and tracking
oszacowanie ustawienia kamery
rekonstrukcja modelu 3D
lokalizacja obiektu
śledzenie obiektu
Opis:
For 3D object localization and tracking with multiple cameras the camera poses have to be known within a high precision. The paper evaluates camera pose estimation via a fundamental matrix and via the known object in environment of multiple static cameras. A special feature point extraction technique based on LED (Light Emitting Diodes) point detection and matching has been developed for this purpose. LED point detection has been solved searching local maximums in images and LED point matching has been solved involving patterned time functions for each light source. Emitting LEDs have been used as sources of known reference points instead of typically used feature point extractors like ORB, SIFT, SURF etc. In such a way the robustness of pose estimation has been obtained. Camera pose estimation is significant for object localization using the networks with multiple cameras which are going to an play increasingly important role in modern Smart Cities environments.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2015, 63, 4; 897-905
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Change Detection for SAR Imagery Using Connected Components Analysis
Autorzy:
Gromek, A.
Jenerowicz, M.
Powiązania:
https://bibliotekanauki.pl/articles/227323.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
change detection
TSX
SAR image analysis
remote sensing
Opis:
Objective of the described analysis is to provide consistent change detection method based on image processing techniques applied to the Synthetic Aperture Radar (SAR) images acquired over the same geographical area, but at two different time instances. The approach adopted in our work requires incorporation of results with the additional information derived from analysis based on mathematical morphology (MM) techniques and visual interpretation of multitemporal VHR optical satellite images.
Źródło:
International Journal of Electronics and Telecommunications; 2012, 58, 2; 111-116
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Visual Detection Method of Longitudinal Crack Based on Computer Image Processing During Slab Continuous Casting
Autorzy:
Liu, Y.
Wang, X.
Sun, Y.
Du, F.
Gao, Y.
Wang, F.
Wang, J.
Powiązania:
https://bibliotekanauki.pl/articles/351636.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
longitudinal crack
visual detection
image processing
continuous casting
Opis:
Based on the mould temperature measured by thermocouples during slab continuous casting, a difference of temperature thermograph is developed to detect slab cracks. In order to detect abnormal temperature region caused by longitudinal crack, the suspicious regions are extracted and divided by virtue of computer image processing algorithms, such as threshold segmentation, connected region judgement and boundary tracing. The abnormal regions are then determined and labeled with the eight connected component labeling algorithm. The boundary of abnormal region is also extracted to depict characteristics of longitudinal crack. Based on above researches, longitudinal crack with abnormal temperature region can be detected and is different from other abnormalities. Four samples of temperature drop are picked up to compare with longitudinal crack on the abnormal region formation, length, width, shape, et al. The results show that the abnormal region caused by longitudinal crack has a linear and vertical shape. The height of abnormal region is more than the width obviously. The ratio of height to width is usually larger than that of other temperature drop regions. This method provides a visual and easy way to detect longitudinal crack and other abnormities. Meanwhile it has a positive meaning to the intelligent and visual mould monitoring system of continuous casting.
Źródło:
Archives of Metallurgy and Materials; 2018, 63, 2; 673-680
1733-3490
Pojawia się w:
Archives of Metallurgy and Materials
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Economical methods for measuring road surface roughness
Autorzy:
Grabowski, D.
Szczodrak, M.
Czyżewski, A.
Powiązania:
https://bibliotekanauki.pl/articles/221297.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
image processing
neural networks
pothole detection
Kinect
Raspberry Pi
Opis:
Two low-cost methods of estimating the road surface condition are presented in the paper, the first one based on the use of accelerometers and the other on the analysis of images acquired from cameras installed in a vehicle. In the first method, miniature positioning and accelerometer sensors are used for evaluation of the road surface roughness. The device designed for installation in vehicles is composed of a GPS receiver and a multi-axis accelerometer. The measurement data were collected from recorded ride sessions taken place on diversified road surface roughness conditions and at varied vehicle speeds on each of examined road sections. The data were gathered for various vehicle body types and afterwards successful attempts were made in constructing the road surface classification employing the created algorithm. In turn, in the video method, a set of algorithms processing images from a depth camera and RGB cameras were created. A representative sample of the material to be analysed was obtained and a neural network model for classification of road defects was trained. The research has shown high effectiveness of applying the digital image processing to rejection of images of undamaged surface, exceeding 80%. Average effectiveness of identification of road defects amounted to 70%. The paper presents the methods of collecting and processing the data related to surface damage as well as the results of analyses and conclusions.
Źródło:
Metrology and Measurement Systems; 2018, 25, 3; 533-549
0860-8229
Pojawia się w:
Metrology and Measurement Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Method for Filling and Sharpening False Colour Layers of Dual Energy X-ray Images
Autorzy:
Dmitruk, K.
Mazur, M.
Denkowski, M.
Mikołajczak, P.
Powiązania:
https://bibliotekanauki.pl/articles/227318.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
X-ray imaging
image processing
false colour
object detection
Opis:
An X-ray scanning and image processing have a vast range of applications in the security. An image of a content of some package being passed for example to an airplane or to the court house may help to figure out if there are any dangerous objects inside that package and to avoid possible threatening situation. As the raw X-ray images are not always easy to analyze and interpret, some image processing methods like an object detection, a frequency resolution increase or a pseudocolouring are being used. In this paper, we propose a pseudocoloring improvement over material based approach. By addition of the edge detection methods we fill and sharpen colour layers over the image, making it easier to interpret. We demonstrate the effectiveness of the methods using real data, acquired from a professional dual energy X-ray scanner.
Źródło:
International Journal of Electronics and Telecommunications; 2016, 62, 1; 49-54
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Robotic Mobile Holder (For CAR Dashboards)
Autorzy:
Madhunala, Srilatha
Kanneti, Bhavya
Anathula, Priya
Powiązania:
https://bibliotekanauki.pl/articles/2200722.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
LabVIEW
image processing
Servo Motor
NImyRIO
face detection
phone holder
Opis:
In the current smart tech world, there is an immense need of automating tasks and processes to avoid human intervention, save time and energy. Nowadays, mobile phones have become one of the essential things for human beings either to call someone, connect to the internet, while driving people need mobile phones to receive or make a call, use google maps to know the routes and many more. Normally in cars, mobile holders are placed on the dashboard to hold the mobile and the orientation of the phone needs to be changed according to the driver's convenience manually, but the driver may distract from driving while trying to access mobile phone which may lead to accidents. To solve this problem, an auto adjustable mobile holder is designed in such a way that it rotates according to the movement of the driver and also it can even alert the driver when he feels drowsiness. Image Processing is used to detect the movement of the driver which is then processed using LabVIEW software and NI myRIO hardware. NI Vision development module is used to perform face recognition and servo motors are used to rotate the holder in the required position. Simulation results show that the proposed system has achieved maximum accuracy in detecting faces, drowsiness and finding the position coordinates.
Źródło:
International Journal of Electronics and Telecommunications; 2023, 69, 1; 89--98
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Performance of Unsupervised Change Detection Method Based on PSO and K-means Clustering for SAR Images
Autorzy:
Shehab, Jinan N.
Abdulkadhim, Hussein A.
Powiązania:
https://bibliotekanauki.pl/articles/1844494.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
change detection
k-means clustering
multitemporal satellite image
PSO
Gabor wavelet filter
remote sensing
Opis:
This paper presents unsupervised change detection method to produce more accurate change map from imbalanced SAR images for the same land cover. This method is based on PSO algorithm for image segmentation to layers which classify by Gabor Wavelet filter and then K-means clustering to generate new change map. Tests are confirming the effectiveness and efficiency by comparison obtained results with the results of the other methods. Integration of PSO with Gabor filter and k-means will providing more and more accuracy to detect a least changing in objects and terrain of SAR image, as well as reduce the processing time.
Źródło:
International Journal of Electronics and Telecommunications; 2021, 67, 3; 403-408
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Real-time Foreground Object Detection Combining the PBAS Background Modelling Algorithm and Feedback from Scene Analysis Module
Autorzy:
Kryjak, T.
Komorkiewicz, M.
Gorgon, M.
Powiązania:
https://bibliotekanauki.pl/articles/225985.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
PBAS algorithm
foreground segmentation
foreground object detection
background generation
background subtraction
background modelling
image processing
image analysis
FPGA
connected component analysis
consecutive frame diffrencing
Opis:
The article presents a hardware implementation of the foreground object detection algorithm PBAS (Pixel-Based Adaptive Segmenter) with a scene analysis module. A mechanism for static object detection is proposed, which is based on consecutive frame differencing. The method allows to distinguish stopped foreground objects (e.g. a car at the intersection, abandoned luggage) from false detections (so-called ghosts) using edge similarity. The improved algorithm was compared with the original version on popular test sequences from the changedetection.net dataset. The obtained results indicate that the proposed approach allows to improve the performance of the method for sequences with the stopped objects. The algorithm has been implemented and successfully verified on a hardware platform with Virtex 7 FPGA device. The PBAS segmentation, consecutive frame differencing, Sobel edge detection and advanced one-pass connected component analysis modules were designed. The system is capable of processing 50 frames with a resolution of 720×576 pixels per second.
Źródło:
International Journal of Electronics and Telecommunications; 2014, 60, 1; 61-72
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-line signal change detection for image segmentation with application in the ceramic tile industry
Autorzy:
Sušac, Filip
Matić, Tomislav
Aleksi, Ivan
Keser, Tomislav
Powiązania:
https://bibliotekanauki.pl/articles/2173520.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
segmentation
edge detection
biscuit tile
image processing
visual inspection
ceramic industry
segmentacja
wykrywanie krawędzi
przetwarzanie obrazu
oględziny
przemysł ceramiczny
Opis:
In the ceramic industry, quality control is performed using visual inspection in three different product stages: green, biscuit, and the final ceramic tile. To develop a real-time computer visual inspection system, the necessary step is successful tile segmentation from its background. In this paper, a new statistical multi-line signal change detection (MLSCD) segmentation method based on signal change detection (SCD) method is presented. Through experimental results on seven different ceramic tile image sets, MLSCD performance is analyzed and compared with the SCD method. Finally, recommended parameters are proposed for optimal performance of the MLSCD method.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; e137121, 1--11
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-line signal change detection for image segmentation with application in the ceramic tile industry
Autorzy:
Sušac, Filip
Matić, Tomislav
Aleksi, Ivan
Keser, Tomislav
Powiązania:
https://bibliotekanauki.pl/articles/2173620.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
segmentation
edge detection
biscuit tile
image processing
visual inspection
ceramic industry
segmentacja
wykrywanie krawędzi
przetwarzanie obrazu
oględziny
przemysł ceramiczny
Opis:
In the ceramic industry, quality control is performed using visual inspection in three different product stages: green, biscuit, and the final ceramic tile. To develop a real-time computer visual inspection system, the necessary step is successful tile segmentation from its background. In this paper, a new statistical multi-line signal change detection (MLSCD) segmentation method based on signal change detection (SCD) method is presented. Through experimental results on seven different ceramic tile image sets, MLSCD performance is analyzed and compared with the SCD method. Finally, recommended parameters are proposed for optimal performance of the MLSCD method.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; art. no. e137121
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
U-Net based frames partitioning and volumetric analysis for kidney detection in tomographic images
Autorzy:
Les, Tomasz
Powiązania:
https://bibliotekanauki.pl/articles/2173575.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
kidney detection
medical image processing
U-net
frames partitioning
volumetric analysis
wykrywanie nerek
przetwarzanie obrazu medycznego
partycjonowanie ramek
analiza objętościowa
Opis:
This work presents an automatic system for generating kidney boundaries in computed tomography (CT) images. This paper presents the main points of medical image processing, which are the parts of the developed system. The U-Net network was used for image segmentation, which is now widely used as a standard solution for many medical image processing tasks. An innovative solution for framing the input data has been implemented to improve the quality of the learning data as well as to reduce the size of the data. Precision-recall analysis was performed to calculate the optimal image threshold value. To eliminate false-positive errors, which are a common issue in segmentation based on neural networks, the volumetric analysis of coherent areas was applied. The developed system facilitates a fully automatic generation of kidney boundaries as well as the generation of a three-dimensional kidney model. The system can be helpful for people who deal with the analysis of medical images, medical specialists in medical centers, especially for those who perform the descriptions of CT examination. The system works fully automatically and can help to increase the accuracy of the performed medical diagnosis and reduce the time of preparing medical descriptions.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; art. no. e137051
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
U-Net based frames partitioning and volumetric analysis for kidney detection in tomographic images
Autorzy:
Les, Tomasz
Powiązania:
https://bibliotekanauki.pl/articles/2090740.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
kidney detection
medical image processing
U-net
frames partitioning
volumetric analysis
wykrywanie nerek
przetwarzanie obrazu medycznego
partycjonowanie ramek
analiza objętościowa
Opis:
This work presents an automatic system for generating kidney boundaries in computed tomography (CT) images. This paper presents the main points of medical image processing, which are the parts of the developed system. The U-Net network was used for image segmentation, which is now widely used as a standard solution for many medical image processing tasks. An innovative solution for framing the input data has been implemented to improve the quality of the learning data as well as to reduce the size of the data. Precision-recall analysis was performed to calculate the optimal image threshold value. To eliminate false-positive errors, which are a common issue in segmentation based on neural networks, the volumetric analysis of coherent areas was applied. The developed system facilitates a fully automatic generation of kidney boundaries as well as the generation of a three-dimensional kidney model. The system can be helpful for people who deal with the analysis of medical images, medical specialists in medical centers, especially for those who perform the descriptions of CT examination. The system works fully automatically and can help to increase the accuracy of the performed medical diagnosis and reduce the time of preparing medical descriptions.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; e137051, 1--9
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Deep learning-based framework for tumour detection and semantic segmentation
Autorzy:
Kot, Estera
Krawczyk, Zuzanna
Siwek, Krzysztof
Królicki, Leszek
Czwarnowski, Piotr
Powiązania:
https://bibliotekanauki.pl/articles/2128156.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
deep learning
medical imaging
tumour detection
semantic segmentation
image fusion
technika deep learning
głęboka nauka
obrazowanie medyczne
wykrywanie guza
segmentacja semantyczna
połączenie obrazu
Opis:
For brain tumour treatment plans, the diagnoses and predictions made by medical doctors and radiologists are dependent on medical imaging. Obtaining clinically meaningful information from various imaging modalities such as computerized tomography (CT), positron emission tomography (PET) and magnetic resonance (MR) scans are the core methods in software and advanced screening utilized by radiologists. In this paper, a universal and complex framework for two parts of the dose control process – tumours detection and tumours area segmentation from medical images is introduced. The framework formed the implementation of methods to detect glioma tumour from CT and PET scans. Two deep learning pre-trained models: VGG19 and VGG19-BN were investigated and utilized to fuse CT and PET examinations results. Mask R-CNN (region-based convolutional neural network) was used for tumour detection – output of the model is bounding box coordinates for each object in the image – tumour. U-Net was used to perform semantic segmentation – segment malignant cells and tumour area. Transfer learning technique was used to increase the accuracy of models while having a limited collection of the dataset. Data augmentation methods were applied to generate and increase the number of training samples. The implemented framework can be utilized for other use-cases that combine object detection and area segmentation from grayscale and RGB images, especially to shape computer-aided diagnosis (CADx) and computer-aided detection (CADe) systems in the healthcare industry to facilitate and assist doctors and medical care providers.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; e136750, 1--7
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł

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