A low cost barcode recognition method

2006 ◽  
Author(s):  
Ying Hu ◽  
Jin Huang ◽  
Zi Ma
Keyword(s):  
Low Cost ◽  
Recognition Method ◽  
Barcode Recognition

Automatic barcode recognition method based on adaptive edge detection and a mapping model

2016 ◽  
Vol 25 (5) ◽  
pp. 053019
Author(s):  
Hua Yang ◽  
Lianzheng Chen ◽  
Yifan Chen ◽  
Yong Lee ◽  
Zhouping Yin
Keyword(s):  
Edge Detection ◽  
Recognition Method ◽  
Mapping Model ◽  
Barcode Recognition

A Road Grade Recognition Method Based on Longitudinal Acceleration

2013 ◽  
Vol 339 ◽  
pp. 38-44
Author(s):  
Yao Fu ◽  
Wan Hua Ye ◽  
Yu Long Lei ◽  
Zhen Jie Liu ◽  
Hua Bing Zeng
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Dynamics Analysis ◽  
Vehicle Speed ◽  
Recognition Method ◽  
Longitudinal Dynamics ◽  
Longitudinal Acceleration ◽  
Output Torque ◽  
Road Grade ◽  
Vehicle Sensors

A road grade recognition method based on longitudinal acceleration was proposed after longitudinal dynamics analysis. The method based on longitudinal dynamics utilized a real-time engine output torque signal and the real-time vehicle speed signal to calculate road grade. The result of simulation and the vehicle field test showed that the method based on existing vehicle sensors was low cost, simple and feasible, it could identify road grade.

scholarly journals Performance Analysis of ANN based Gait Recognition

2018 ◽  
pp. 112-125 ◽  
Author(s):  
Taniya Sharma ◽  
Satnam Singh Dub ◽  
Bhanu Gupta
Keyword(s):  
Neural Network ◽  
Background Subtraction ◽  
Distance Measure ◽  
Recognition Performance ◽  
Low Cost ◽  
Gait Recognition ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Recognition Method ◽  
Current Frame

It is well-known that biometrics are a powerful tool for reliable automated person identification. Automatic gait recognition is one of the newest of the emergent biometrics and has many advantages over other biometrics. The most notable advantage is that it does not require contact with the subjects nor does it require the subject to be near a camera. This work employs a gait recognition process with binary silhouette-based input images and Artificial Neural Network (ANN) based classification in MATLAB. The performance of the recognition method depends significantly on the quality of the extracted binary silhouettes. In this work, a computationally low-cost fuzzy correlogram based method is employed for background subtraction. Even highly robust background subtraction and shadow elimination algorithms produce erroneous outputs at times with missing body portions, which consequently affect the recognition performance. Frame Difference Energy Image (FDEI) reconstruction is performed to alleviate the detrimental effect of improperly extracted silhouettes and to make the recognition method robust to partial incompleteness. Subsequently, features are extracted via two methods and fed to the BPNN (Back Propagation Neural Network based classifier which uses feature vector (exemplars) to compute similarity scores and carry out identification using weight vectors i.e. Frame-to-Exemplar-Distance (FED) vector. The FED uses the distance measure between pre-determined feature vectors and the weight vectors of the current frame as an identification criterion. The ANN performance is evaluated for recognition and speed parameters at different training gait angles.

scholarly journals Programming of Industrial Robots Using the Recognition of Geometric Signs in Flexible Welding Process

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1429
Author(s):  
Olaf Ciszak ◽  
Jakub Juszkiewicz ◽  
Marcin Suszyński
Keyword(s):  
Computer Program ◽  
Control Systems ◽  
Robot Control ◽  
Low Cost ◽  
Digital Camera ◽  
Welding Process ◽  
Industrial Robots ◽  
Recognition Method ◽  
Geometric Shapes ◽  
Cost System

The purpose of the article was to build a low-cost system for identifying shapes in order to program industrial robots (on the base of the six-axis “ABB IRB 140” robot) for a welding process in 2D. The whole system consisted of several elements developed in individual stages. The first step was to identify the existing robot control systems, which analysed images from an attached low-cost digital camera. Then, a computer program, which handles communication with the digital camera capturing and processing, was written. In addition, the program’s task was to detect geometric shapes (contours) drawn by humans and to approximate them. This study also presents research on a binarization and contour recognition method for this application. Based on this, the robot is able to weld the same contours on a 2D plane.

scholarly journals The Optical Barcode Detection and Recognition Method Based on Visible Light Communication Using Machine Learning

2018 ◽  
Vol 8 (12) ◽  
pp. 2425 ◽  
Author(s):  
Jingyi Li ◽  
Weipeng Guan
Keyword(s):  
Machine Learning ◽  
Visible Light ◽  
Low Cost ◽  
Recognition Rate ◽  
Visible Light Communication ◽  
Oxide Semiconductor ◽  
Support Vector ◽  
Qr Codes ◽  
Recognition Method ◽  
Detection And Recognition

Visible light communication (VLC) has developed rapidly in recent years. VLC has the advantages of high confidentiality, low cost, etc. It could be an effective way to connect online to offline (O2O). In this paper, an RGB-LED-ID detection and recognition method based on VLC using machine learning is proposed. Different from traditional encoding and decoding VLC, we develop a new VLC system with a form of modulation and recognition. We create different features for different LEDs to make it an Optical Barcode (OBC) based on a Complementary Metal-Oxide-Semiconductor (CMOS) senor and a pulse-width modulation (PWM) method. The features are extracted using image processing and then support vector machine (SVM) and artificial neural networks (ANN) are introduced into the scheme, which are employed as a classifier. The experimental results show that the proposed method can provide a huge number of unique LED-IDs with a high LED-ID recognition rate and its performance in dark and distant conditions is significantly better than traditional Quick Response (QR) codes. This is the first time the VLC is used in the field of Internet of Things (IoT) and it is an innovative application of RGB-LED to create features. Furthermore, with the development of camera technology, the number of unique LED-IDs and the maximum identifiable distance would increase. Therefore, this scheme can be used as an effective complement to QR codes in the future.

scholarly journals Abnormal Road Surface Recognition Based on Smartphone Acceleration Sensor

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 451 ◽  
Author(s):  
Ronghua Du ◽  
Gang Qiu ◽  
Kai Gao ◽  
Lin Hu ◽  
Li Liu
Keyword(s):  
Low Cost ◽  
Surface Condition ◽  
Detection Threshold ◽  
Road Surface ◽  
Vehicle Speed ◽  
K Nearest Neighbor ◽  
Recognition Method ◽  
Vibration Acceleration ◽  
The Road ◽  
Surface Recognition

In order to identify the abnormal road surface condition efficiently and at low cost, a road surface condition recognition method is proposed based on the vibration acceleration generated by a smartphone when the vehicle passes through the abnormal road surface. The improved Gaussian background model is used to extract the features of the abnormal pavement, and the k-nearest neighbor (kNN) algorithm is used to distinguish the abnormal pavement types, including pothole and bump. Comparing with the existing works, the influence of vehicles with different suspension characteristics on the detection threshold is studied in this paper, and an adaptive adjustment mechanism based on vehicle speed is proposed. After comparing the field investigation results with the algorithm recognition results, the accuracy of the proposed algorithm is rigorously evaluated. The test results show that the vehicle vibration acceleration contains the road surface condition information, which can be used to identify the abnormal road conditions. The test result shows that the accuracy of the recognition of the road surface pothole is 96.03%, and the accuracy of the road surface bump is 94.12%. The proposed road surface recognition method can be utilized to replace the special patrol vehicle for timely and low-cost road maintenance.

scholarly journals Robust and Accurate Wi-Fi Fingerprint Location Recognition Method Based on Deep Neural Network

2020 ◽  
Vol 10 (1) ◽  
pp. 321 ◽  
Author(s):  
Yifan Wang ◽  
Jingxiang Gao ◽  
Zengke Li ◽  
Long Zhao
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Markov Models ◽  
Low Cost ◽  
Posteriori Probability ◽  
Recognition Method ◽  
Location Recognition ◽  
Wide Availability ◽  
Signal Fluctuation ◽  
Fingerprint Database

Currently, indoor locations based on the received signal strength (RSS) of Wi-Fi are attracting more and more attention thanks to the technology’s low cost, low power consumption and wide availability in mobile devices. However, the accuracy of Wi-Fi positioning is limited, due to the signal fluctuation and indoor multipath interference. In order to overcome this problem, this paper proposes a robust and accurate Wi-Fi fingerprint location recognition method based on a deep neural network (DNN). A stacked denoising auto-encoder (SDAE) is used to extract robust features from noisy RSS to construct a feature-weighted fingerprint database offline. We use the combination of the weights of posteriori probability and geometric relationship of fingerprint points to calculate the coordinates of unknown points online. In addition, we use constrained Kalman filtering and hidden Markov models (HMM) to smooth and optimize positioning results and overcome the influence of gross error on positioning results, combined with characteristics of user movement in buildings, both dynamic and static. The experiment shows that the DNN is feasible for position recognition, and the method proposed in this paper is more accurate and stable than the commonly used Wi-Fi positioning methods in different scenes.

Decomposition of the metastable beta titanium alloy Ti-15-3

1983 ◽  
Vol 41 ◽  
pp. 264-265
Author(s):  
Y. L. Chen ◽  
S. Fujlshiro
Keyword(s):  
Low Cost ◽  
High Strength ◽  
Alpha Phase ◽  
Thick Sheet ◽  
Omega Phase ◽  
Beta Titanium Alloy ◽  
Beta Titanium ◽  
Beta Matrix ◽  
Metastable Beta ◽  
Very High

Metastable beta titanium alloys have been known to have numerous advantages such as cold formability, high strength, good fracture resistance, deep hardenability, and cost effectiveness. Very high strength is obtainable by precipitation of the hexagonal alpha phase in a bcc beta matrix in these alloys. Precipitation hardening in the metastable beta alloys may also result from the formation of transition phases such as omega phase. Ti-15-3 (Ti-15V- 3Cr-3Al-3Sn) has been developed recently by TIMET and USAF for low cost sheet metal applications. The purpose of the present study was to examine the aging characteristics in this alloy.The composition of the as-received material is: 14.7 V, 3.14 Cr, 3.05 Al, 2.26 Sn, and 0.145 Fe. The beta transus temperature as determined by optical metallographic method was about 770°C. Specimen coupons were prepared from a mill-annealed 1.2 mm thick sheet, and solution treated at 827°C for 2 hr in argon, then water quenched. Aging was also done in argon at temperatures ranging from 316 to 616°C for various times.

Chromic Acid Etching of Polyethylene

1973 ◽  
Vol 31 ◽  
pp. 72-73
Author(s):  
J. D. Muzzy ◽  
R. D. Hester ◽  
J. L. Hubbard
Keyword(s):  
Chromic Acid ◽  
Low Cost ◽  
Acid Etching ◽  
Crystalline Morphology ◽  
Bulk Specimen ◽  
Morphological Studies ◽  
Perfect Form ◽  
Molecular Length ◽  
Lamellar Texture ◽  
Cost Studies

Polyethylene is one of the most important plastics produced today because of its good physical properties, ease of fabrication and low cost. Studies to improve the properties of polyethylene are leading to an understanding of its crystalline morphology. Polyethylene crystallized by evaporation from dilute solutions consists of thin crystals called lamellae. The polyethylene molecules are parallel to the thickness of the lamellae and are folded since the thickness of the lamellae is much less than the molecular length. This lamellar texture persists in less perfect form in polyethylene crystallized from the melt.Morphological studies of melt crystallized polyethylene have been limited due to the difficulty of isolating the microstructure from the bulk specimen without destroying or deforming it.

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