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

A Robotic Facial Expression Recognition System Using Real-Time Vision System

2008 ◽  
Vol 381-382 ◽  
pp. 375-378
Author(s):  
K.T. Song ◽  
M.J. Han ◽  
F.Y. Chang ◽  
S.H. Chang
Keyword(s):  
Image Processing ◽  
Facial Expression ◽  
Real Time ◽  
Facial Expressions ◽  
Facial Expression Recognition ◽  
Vision System ◽  
Recognition System ◽  
Expression Recognition ◽  
On Line ◽  
Processing Platform

The capability of recognizing human facial expression plays an important role in advanced human-robot interaction development. Through recognizing facial expressions, a robot can interact with a user in a more natural and friendly manner. In this paper, we proposed a facial expression recognition system based on an embedded image processing platform to classify different facial expressions on-line in real time. A low-cost embedded vision system has been designed and realized for robotic applications using a CMOS image sensor and digital signal processor (DSP). The current design acquires thirty 640x480 image frames per second (30 fps). The proposed emotion recognition algorithm has been successfully implemented on the real-time vision system. Experimental results on a pet robot show that the robot can interact with a person in a responding manner. The developed image processing platform is effective for accelerating the recognition speed to 25 recognitions per second with an average on-line recognition rate of 74.4% for five facial expressions.

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

The Research and Implementation of Parallel In-Vehicle Vision System Based on Multi-Core Processors

2012 ◽  
Vol 224 ◽  
pp. 529-532
Author(s):  
Zhi Tao Dai ◽  
Yi Wen Wang ◽  
Shu Sun ◽  
Pan Zhang
Keyword(s):  
Vision System ◽  
Recognition System ◽  
Parallel Processor ◽  
Hardware Platform ◽  
Traffic Signs ◽  
Vehicle Traffic ◽  
Traffic Lights

This paper introduces a novel implementation of in-vehicle traffic signs and traffic lights recognition system based on FPGA multi-core processers. Images could be processed with multi-core parallel processor using the corresponding relationships of traffic signs’ color and shape. We implement this vehicle vision system on SOPC hardware platform.

scholarly journals Performance Analysis of Target Information Recognition System for Agricultural Robots

2021 ◽  
Vol 12 (2) ◽  
pp. 49-60
Author(s):  
Yun Ji ◽  
Rajeev Kumar ◽  
Daljeet Singh ◽  
Maninder Singh
Keyword(s):  
Decision Making ◽  
Production Efficiency ◽  
Vision System ◽  
Recognition Rate ◽  
Robot Vision ◽  
Recognition System ◽  
Economic Benefits ◽  
Prototype System ◽  
Target Information ◽  
Information Recognition

In this paper, an agricultural robot vision system is proposed for two typical environments—farmland and orchard—combined with weeding between crops. The system includes orchard production monitoring and prediction tasks, the target information recognition approach, and visual servo decision making. The results obtained from the proposed system show that using the region combination features of image 2D histogram as the decision-making basis, the accurate and rapid indirect identification and positioning of crop seedlings can be accomplished while skipping the complex process of accurately identifying crops and weeds. The algorithm performs reasonably good as the time of target recognition in the prototype system is found to be less than 16 ms, and the average accurate recognition rate of 97.43% is achieved. The benefits of the proposed system are the continuous improvement of the quality of agricultural products, the rise of production efficiency, and the increase of economic benefits.

Ensemble Learning based Age Invariant Fea-ture Recognition Using Soft Computing

2021 ◽  
pp. 7278-7290
Author(s):  
Divyanshu Sinha, Dr J. P. Pandey, Dr. Bhavesh Chauhan
Keyword(s):  
Support Vector Machine ◽  
Face Recognition ◽  
Recognition System ◽  
Support Vector ◽  
Matlab Simulation ◽  
Automated Recognition ◽  
Face Recognition System ◽  
Proposed Model ◽  
Overall Performance ◽  
Vision Application

Face recognition system is a state-of-the-art computer vision application within the artificial intelligence arena. Face recognition is the automated recognition of humans for their names/unique ID. The age invariant face recognition is a challenge task in the field of face recog-nition. In this work, we have introduced a stacked support vector machine where kernel activation of prototype examples is combined in nonlinear ways. The proposed work integrates soft compu-ting-based support vector machine (SVM) with deep SVM. The proposed model uses the implied relation between the variables described above in order to optimize their overall performance. Specifically, our method uses three different stages of complex convolution neural networks that detect and analyze the location of faces position and landmarks. This work has introduced cross-age celebrity dataset (CACD) for both single as well as cross-database enabling the transition of age. The proposed work has been implemented in the MATLAB simulation tool considering CACD dataset. Experimental results indicate that our techniques significantly outperform other strategies across a range of challenging metrics.

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.

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