A Parallel Partial Enhancement Method for License Plate Localization in Low-Quality Images

2021 ◽  
pp. 2150301
Author(s):  
Sainan Xiao ◽  
Wangdong Yang ◽  
Buwen Cao ◽  
Honglie Zhou ◽  
Chenjun He
Keyword(s):  
Color Difference ◽  
Industrial Applications ◽  
License Plate ◽  
Real Time Processing ◽  
Color Ratio ◽  
Quality Image ◽  
Speed Performance ◽  
Enhancement Method ◽  
Projection Analysis ◽  
Performance Of Algorithm

Finding an effective license plate localization (LPL) method is challenging owing to different conditions during the image acquisition phase. Most existing methods do not consider various low-quality image conditions that exist in real-world situations. Low-quality image conditions mean that an image can have low resolution, plate imperfection effects, variable illumination environments or background objects similar to the license plate (LP). To improve the anti-interference ability and the speed performance of algorithm, this study aims to develop a parallel partial enhancement method based on color differences that demonstrates improved localization performance for blue–white LP images under low-quality conditions. A novel color difference model is exploited to enhance LP areas and filter non-LP areas. Blue–white color ratio and projection analysis are performed to select the exact LP area from the candidates. Moreover, this study develops a parallel version based on a multicore CPU for real-time processing for industrial applications. An image database including 395 low-quality car images captured from various scenes under different conditions is tested for the performance evaluation. The extensive experiments show the effectiveness and efficiency of the proposed approach.

Study on Image Enhancement Technique of License Plate Recognition

2015 ◽  
Vol 738-739 ◽  
pp. 678-681
Author(s):  
Yu Bing Dong ◽  
Guang Liang Cheng ◽  
Ming Jing Li
Keyword(s):  
Image Enhancement ◽  
License Plate ◽  
Gray Level ◽  
License Plate Recognition ◽  
Median Filtering ◽  
Enhancement Technique ◽  
Enhancement Method ◽  
Basic Image

Various basic image enhancement techniques of License Plate Recognition are discussed and simulated with MATLAB. Through a lot of experiments, an improved image enhancement method is proposed by combining gray-level transformation and median filtering. The method can efficiently avoid interfere and enhance the contrast of image and obtain satisfying effects.

Assessment of Some Enhancement Methods of Renal X-ray Image

2020 ◽  
Vol 18 (12) ◽  
pp. 01-05
Author(s):  
Salim J. Attia
Keyword(s):  
Image Quality ◽  
Radiation Dosage ◽  
Histogram Equalization ◽  
Quality Factors ◽  
X Ray ◽  
Adaptive Histogram Equalization ◽  
Quality Image ◽  
Enhancement Method ◽  
Spatial Quality

The study focuses on assessment of the quality of some image enhancement methods which were implemented on renal X-ray images. The enhancement methods included Imadjust, Histogram Equalization (HE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The images qualities were calculated to compare input images with output images from these three enhancement techniques. An eight renal x-ray images are collected to perform these methods. Generally, the x-ray images are lack of contrast and low in radiation dosage. This lack of image quality can be amended by enhancement process. Three quality image factors were done to assess the resulted images involved (Naturalness Image Quality Evaluator (NIQE), Perception based Image Quality Evaluator (PIQE) and Blind References Image Spatial Quality Evaluator (BRISQE)). The quality of images had been heightened by these methods to support the goals of diagnosis. The results of the chosen enhancement methods of collecting images reflected more qualified images than the original images. According to the results of the quality factors and the assessment of radiology experts, the CLAHE method was the best enhancement method.

scholarly journals Design and implementation of wireless system for vibration fault detection using fuzzy logic

2020 ◽  
Vol 9 (3) ◽  
pp. 545
Author(s):  
Moneer Ali Lilo ◽  
Maath Jasem Mahammad
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Industrial Applications ◽  
Vibration Sensor ◽  
Fault Classification ◽  
Maintenance Cost ◽  
Wireless System ◽  
Real Time Processing ◽  
Time Processing ◽  
Fuzzy Logic Technique

This paper aims at constructing the wireless system for fault detecting and monitoring by computer depending on the wireless and fuzzy logic technique. Wireless applications are utilized to identify, classify, and monitor faults in the real time to protect machines from damage .Two schemes were tested; first scheme fault collected X-Y-Z-axes mode while the second scheme collected Y-axis mode, which is utilized to protect the induction motor (IM) from vibrations fault. The vibration signals were processed in the central computer to reduce noise by signal processing stage, and then the fault was classified and monitored based on Fuzzy Logic (FL). The wireless vibration sensor was designed depending on the wireless techniques and C++ code. A fault collection, noise reduction, vibration fault classification and monitoring were implemented by MATLAB code.  In the second scheme the processed real time was reduced to 60%, which is included collection, filtering, and monitoring fault level. Results showed that the system has the ability to early detect the fault if appears on the machine with time processing of 1.721s. This work will reduce the maintenance cost and provide the ability to utilize the system with harsh industrial applications to diagnose the fault in real time processing.

scholarly journals Automatic Vehicle License Plate Extraction Using Region-Based Convolutional Neural Networks and Morphological Operations

Symmetry ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 882 ◽  
Author(s):  
JongBae Kim
Keyword(s):  
Real Time ◽  
Detection Rate ◽  
Input Image ◽  
License Plate ◽  
Morphological Operations ◽  
Morphological Operation ◽  
Edge Pixel ◽  
Real Time Processing ◽  
Time Processing ◽  
Candidate Regions

The number and range of the candidate vehicle license plate (VLP) region affects the result of the VLP extraction symmetrically. Therefore, in order to improve the VLP extraction rate, many candidate VLP regions are selected. However, there is a problem that the processing time increases symmetrically. In this paper, we propose a method that allows detecting a vehicle license plate in the real-time mode. To do this, the proposed method makes use of the region-based convolutional neural network (R-CNN) method and morphological operations. The R-CNN method is a deep learning method that selects a large number of candidate regions from an input image and compares them to determine whether objects of interest are included. However, this method has limitations when used in real-time processing. Therefore, to address this limitation in the proposed method, while selecting a candidate vehicle region, the selection range is reduced based on the size and position of the vehicle in the input image; hence, processing can be performed quickly. A vehicle license plate is detected by performing a morphological operation based on the edge pixel distribution of the detected vehicle region. Experimental results show that the detection rate of vehicles is approximately 92% in real road environments, and the detection rate of vehicle license plates is approximately 83%.

RIDED-2D: A RULE-BASED INSTANTANEOUS DENOISING AND EDGE DETECTION METHOD FOR 2D RANGE SCAN LINE

2011 ◽  
Vol 25 (06) ◽  
pp. 807-833 ◽  
Author(s):  
JIAN WANG ◽  
ZHEN-QIANG YAO ◽  
QUAN-ZHANG AN ◽  
YAO-JIE ZHU ◽  
XUE-PING ZHANG ◽  
...  
Keyword(s):  
Edge Detection ◽  
Industrial Applications ◽  
Detection Methods ◽  
Range Image ◽  
Range Images ◽  
Basic Step ◽  
Real Time Processing ◽  
Mixed Pixels ◽  
Edge Points ◽  
Scan Line

Edge detection is often regarded as a basic step in range image processing by virtue of its crucial effect. The majority of existing edge detection methods cannot satisfy the requirement of efficiency in many industrial applications due to huge computational costs. In this paper, a novel instantaneous method, named RIDED-2D is proposed for denoising and edge detection for 2D scan line in range images. In the method, silhouettes of 2D scan line are classified into eight types by defining a few new coefficients. Several discriminant criteria on large noise filtering and edge detection are stipulated based on qualitative feature analysis on each type. Selecting some feature point candidates, a practical parameter learning method is provided to determine the threshold set, along with the implementation of an integrated algorithm by merging calculation steps. Because all the coefficients are established based on distances among the points or their ratio, RIDED-2D is inherently invariant to translation and rotation transformations. Furthermore, a forbidden region approach is proposed to eliminate interference of the mixed pixels. Key performances of RIDED-2D are evaluated in detail by including computational complexity, time expenditure, accuracy and stability. The results indicate that RIDED-2D can detect edge points accurately from several real range images, in which large noises and systematic noises are involved, and the total processing time is less than 0.1 millisecond on an ordinary PC platform using the integrated algorithm. Comparing with other state-of-the-art edge detection methods qualitatively, RIDED-2D exhibits a prominent advantage on computational efficiency. Thus, the proposed method qualifies for real-time processing in stringent industrial applications. Besides, another contribution of this paper is to introduce CPU clock counting technique to evaluate the performance of the proposed algorithm, and suggest a convenient and objective way to estimate the algorithm's time expenditure in other platforms.

scholarly journals Hand Gesture Recognition Algorithm Using SVM and HOG Model for Control of Robotic System

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Phat Nguyen Huu ◽  
Tan Phung Ngoc
Keyword(s):  
Gesture Recognition ◽  
Processing Speed ◽  
Industrial Applications ◽  
Recognition Algorithm ◽  
Robotic System ◽  
Support Vector ◽  
Histogram Of Oriented Gradient ◽  
Real Time Processing ◽  
Vector Machines ◽  
The Status

In this study, we propose the gesture recognition algorithm using support vector machines (SVM) and histogram of oriented gradient (HOG). Besides, we also use the CNN model to classify gestures. We approach and select techniques of applying problem controlling for the robotic system. The goal of the algorithm is to detect gestures with real-time processing speed, minimize interference, and reduce the ability to capture unintentional gestures. Static gesture controls are used in this study including on, off, increasing, and decreasing. Besides, it uses motion gestures including turning on the status switch and increasing and decreasing the volume. Results show that the algorithm is up to 99% accuracy with a 70-millisecond execution time per frame that is suitable for industrial applications.

scholarly journals Classification and Comparison of License Plates Localization Algorithms

2021 ◽  
Vol 12 (2) ◽  
pp. 1-11
Author(s):  
Mustapha Saidallah ◽  
Fatimazahra Taki ◽  
Abdelbaki El Belrhiti El Alaoui ◽  
Abdeslam El Fergougui
Keyword(s):  
Information And Communication Technologies ◽  
Intelligent Transportation Systems ◽  
Transportation Systems ◽  
Transport Sector ◽  
License Plate ◽  
Economic Competition ◽  
Real Time Processing ◽  
Localization Algorithms ◽  
New Information ◽  
Information And Communication

The Intelligent Transportation Systems (ITS) are the subject of a world economic competition. They are the application of new information and communication technologies in the transport sector, to make the infrastructures more efficient, more reliable and more ecological. License Plates Recognition (LPR) is the key module of these systems, in which the License Plate Localization (LPL) is the most important stage, because it determines the speed and robustness of this module. Thus, during this step the algorithm must process the image and overcome several constraints as climatic and lighting conditions, sensors and angles variety, LPs’ no-standardization, and the real time processing. This paper presents a classification and comparison of License Plates Localization (LPL) algorithms and describes the advantages, disadvantages and improvements made by each of them.

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