MUSER: A prototype musical score recognition system using mathematical morphology

1993 ◽  
Vol 6 (2-3) ◽  
pp. 140-150 ◽  
Author(s):  
Bharath R. Modayur ◽  
Visvanathan Ramesh ◽  
Robert M. Haralick ◽  
Linda G. Shapiro
Keyword(s):  
Mathematical Morphology ◽  
Recognition System ◽  
Musical Score

scholarly journals Use of Mathematical Morphology in Vehicle Plate Detection

2018 ◽  
Vol 11 (4) ◽  
pp. 195-200
Author(s):  
NEERAJA MOHANAN ◽  
AFAQ AHMAD ◽  
SAYYID SAMIR AL-BUSAIDI ◽  
LAZHAR KHIRIJI ◽  
AMIR ABDULGHANI ◽  
...  
Keyword(s):  
Mathematical Morphology ◽  
Traffic Control ◽  
Traffic Management ◽  
Detection System ◽  
Software Tool ◽  
Recognition System ◽  
Continuous Increase ◽  
The Road ◽  
Toll Collection ◽  
On The Road

In the past couple of decades, the number of vehicles has increased radically. A statistic which presents the number of cars sold worldwide from 1990 through 2017, forecasts for 2018, some 81.6 million automobiles are expected to be sold by the end 2018. With this continuous increase, it is becoming very tedious to keep track of each vehicle for the purpose of security, law enforcement and traffic management. This phenomenon of rapidly increasing vehicles on the road highlights the importance for a vehicle number plate recognition system. By recognizing the car plates, the drivers of the vehicle can be identified from the database. Number plate detection system are used in various applications like traffic law maintenance, traffic control, automatic toll collection, parking systems, automatic gate openers. This paper presents a unique algorithmic procedure for detecting vehicle plate number which is based on the concept of mathematical morphology. The developed algorithm is simple, efficient and flexible. The algorithm is capable of working satisfactorily even in different constraints such as like rain, smoke and shadow. This user-friendly software tool is developed on MATLAB platform which is one of the common and efficient image processing analysis tools.

Research on Pre-Processing Methods for License Plate Recognition

2021 ◽  
Vol 11 (1) ◽  
pp. 47-79
Author(s):  
Weifang Zhai ◽  
Terry Gao ◽  
Juan Feng
Keyword(s):  
Edge Detection ◽  
Mathematical Morphology ◽  
Traffic Management ◽  
Recognition System ◽  
Character Segmentation ◽  
License Plate ◽  
License Plate Recognition ◽  
Vertical Projection ◽  
License Plate Location ◽  
Plate Location

The license plate recognition technology is an important part of the construction of an intelligent traffic management system. This paper mainly researches the image preprocessing, license plate location, and character segmentation in the license plate recognition system. In the preprocessing part of the image, the edge detection method based on convolutional neural network (CNN) is used for edge detection. In the design of the license plate location, this paper proposes a location method based on a combination of mathematical morphology and statistical jump points. First, the license plate area is initially located using mathematical morphology-related operations and then the location of the license plate is accurately located using statistical jump points. Finally, the plate with tilt is corrected. In the process of character segmentation, the border and delimiter are first removed, then the character vertical projection method and the character boundary are used to segment the character for actually using cases.

AN OPTICAL MUSIC RECOGNITION SYSTEM FOR SKEW OR INVERTED MUSICAL SCORES

2013 ◽  
Vol 27 (07) ◽  
pp. 1353005 ◽  
Author(s):  
YUNG-SHENG CHEN ◽  
FENG-SHENG CHEN ◽  
CHIN-HUNG TENG
Keyword(s):  
Image Processing ◽  
Recognition Accuracy ◽  
Recognition System ◽  
Pop Music ◽  
Musical Score ◽  
Optical Music Recognition ◽  
Pattern Recognition Techniques ◽  
Musical Scores ◽  
Music Recognition ◽  
Series Of Experiments

Optical Music Recognition (OMR) is a technique for converting printed musical documents into computer readable formats. In this paper, we present a simple OMR system that can perform well for ordinary musical documents such as ballad and pop music. This system is constructed based on fundamental image processing and pattern recognition techniques, thus it is easy to implement. Moreover, this system has a strong capability in skew restoration and inverted musical score detection. From a series of experiments, the error for our skew restoration is below 0.2° for any possible document rotation and the accuracy of inverted musical score detection is up to 98.89%. The overall recognition accuracy of our OMR can achieve to nearly 97%, a figure comparable with current commercial OMR software. However, if taking into image skew into consideration, our system is superior to commercial software in terms of recognition accuracy.

Extraction of License Plate Region in License Plate Recognition System

2013 ◽  
Vol 441 ◽  
pp. 655-659
Author(s):  
Yuan Ning ◽  
Yao Wen Liu ◽  
Yan Bin Zhang ◽  
Hao Yuan
Keyword(s):  
Edge Detection ◽  
Mathematical Morphology ◽  
Recognition System ◽  
Intelligent Vehicle ◽  
License Plate ◽  
License Plate Recognition ◽  
Important Stage ◽  
System A ◽  
Average Accuracy ◽  
Extraction Algorithm

Extraction of License plate region is an important stage in the intelligent vehicle license plate recognition system. A practical license plate extraction algorithm based on edge detection and mathematical morphology is presented, the algorithm mainly consists of six modules: pre-processing, edge detection, binaryzation and denoising, morphology operation, filtration of connected regions, finding license plate region. From the experiments, the algorithm can detect the region of license plate quickly with 98% average accuracy of locating vehicle license plate region.

scholarly journals Automated recognition system of musical score (vision system of the WABOT-2)

1985 ◽  
Vol 3 (4) ◽  
pp. 354-361 ◽  
Author(s):  
Toshiaki MATSUSHIMA ◽  
Katsuhiro KANAMORI ◽  
Sadamu OHTERU
Keyword(s):  
Vision System ◽  
Recognition System ◽  
Musical Score ◽  
Automated Recognition

NEURAL NETWORKS FOR THE RECOGNITION OF ENGRAVED MUSICAL SCORES

1992 ◽  
Vol 06 (01) ◽  
pp. 193-208 ◽  
Author(s):  
PHILIPPE MARTIN ◽  
CAMILLE BELLISSANT
Keyword(s):  
Image Analysis ◽  
Recognition System ◽  
Connected Components ◽  
Multilayer Perceptrons ◽  
Musical Score ◽  
Analysis Techniques ◽  
Musical Scores ◽  
Skeleton Graph ◽  
Classical Image ◽  
Image Analysis Techniques

The image analysis levels of a recognition system for engraved musical scores are described. Recognizing musical score images requires an accurate segmentation stage to isolate symbols from staff lines. This symbols/staves segregation is achieved by the use of inscribed line (chord) information. This information, processed by a multilayer perceptron, allows an efficient segmentation in terms of the remaining connected components. Some of these components are then classified, using another network, according to a coding of their skeleton graph. Special attention is paid to the design of the networks: the architectures are adapted to the specificities of each task. Multilayer perceptrons are employed here together with other more classical image analysis techniques which are also presented.

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