Classification of Sketch Strokes and Corner Detection Using Conic Sections and Adaptive Clustering

1997 ◽  
Vol 119 (1) ◽  
pp. 131-135 ◽  
Author(s):  
M. Shpitalni ◽  
H. Lipson
Keyword(s):  
Adaptive Method ◽  
Corner Detection ◽  
Conic Section ◽  
Context Analysis ◽  
Natural Classification ◽  
Adaptive Clustering ◽  
Noisy Input ◽  
Classification Property ◽  
On Line

This paper presents a method for classifying pen strokes in an on-line sketching system. The method, based on linear least squares fitting to a conic section equation, proposes using the conic equation’s natural classification property to help classify sketch strokes and identify lines, elliptic arcs, and corners composed of two lines with an optional fillet. The hyperbola form of the conic equation is used for corner detection. The proposed method has proven to be fast, suitable for real-time classification, and capable of tolerating noisy input, including cusps and spikes. The classification is obtained in o(n) time in a single path, where n is the number of sampled points. In addition, an improved adaptive method for clustering disconnected end-points is proposed. The notion of in-context analysis is discussed, and examples from a working implementation are given.

A Hybrid Methodology For On-Line Process Monitoring

2004 ◽  
Vol 2 (1) ◽  
Author(s):  
Rakesh Kumar ◽  
Avinash M. Jade ◽  
Valadi K. Jayaraman ◽  
Bhaskar D. Kulkarni
Keyword(s):  
Process Monitoring ◽  
Current Practice ◽  
Locally Linear Embedding ◽  
Support Vector ◽  
Nonlinear Dimensionality Reduction ◽  
Hybrid Strategy ◽  
Vector Machines ◽  
On Line ◽  
Line Process

A hybrid strategy of using (i) locally linear embedding for nonlinear dimensionality reduction of high dimensional data and (ii) support vector machines for classification of the resultant features is proposed as a robust methodology for process monitoring. Illustrative examples substantiate the methodology vis-à-vis current practice.

Detection of Roller Bearing Conditions Using Mechatronics Approach

1999 ◽  
Author(s):  
T. I. Liu ◽  
F. Ordukhani
Keyword(s):  
Neural Networks ◽  
Roller Bearing ◽  
Diagnostic System ◽  
Feature Selection Technique ◽  
Vibration Signals ◽  
Selection Technique ◽  
On Line ◽  
Line Classification ◽  
Nonlinear Pattern

Abstract An on-line monitoring and diagnostic system is needed to detect faulty bearings. In this work, by applying the feature selection technique to the data obtained from vibration signals, six indices were selected. Artificial neural networks were used for nonlinear pattern recognition. An attempt was made to distinguish between normal and defective bearings. Counterpropagation neural networks with various network sizes were trained for these tasks. The counterpropagation neural networks were able to recognize a normal from a defective bearing with the success rate between 88.3% to 100%. The best results were obtained when all the six indices were used for the on-line classification of roller bearings.

Robust text watermarking based on line shifting

2020 ◽  
Vol 7 (1) ◽  
pp. 3-13
Author(s):  
Alexander Kozachok ◽  
Sergey Kopylov
Keyword(s):  
Block Diagram ◽  
Data Embedding ◽  
Process Data ◽  
Text Data ◽  
Data Format ◽  
Robust Watermark ◽  
Watermark Embedding ◽  
Line Spacing ◽  
On Line

 Abstract— This article presents an approach to protection of printed text data by watermark embedding in the printing process. Data protection is based on robust watermark embedding that is invariant to text data format converting into image. The choice of a robust watermark within the confines of the presented classification of digital watermark is justified. The requirements to developed robust watermark have been formed. According to the formed requirements and existing restrictions, an approach to robust watermark embedding into text data based on a steganographic algorithm of line spacing shifting has been developed. The block diagram and the description of the developed algorithm of data embedding into text data are given. An experimental estimation of the embedding capacity and perceptual invisibility of the developed data embedding approach was carried out. An approach to extract embedded information from images containing a robust watermark has been developed. The limits of the retrieval, extraction accuracy and robustness evaluation of embedded data to various transformations have been experimentally established.Tóm tắt— Bài báo trình bày cách tiếp cận để bảo vệ dữ liệu văn bản in bằng cách nhúng vào văn bản một đoạn thủy vân trong quá trình in. Bảo vệ dữ liệu dựa trên việc sử dụng thủy vân bền vững có khả năng chống lại sự chuyển đổi định dạng dữ liệu văn bản sang dữ liệu hình ảnh. Sau quá trình phân tích các hệ thống thủy vân số hiện có, nhận thấy việc lựa chọn một mô hình thủy vân bền vững là hợp lý. Do yêu cầu thực tế và các hạn chế của phương pháp nhúng thủy vân vào dữ liệu văn bản hiện có, bài báo đưa ra phương pháp nhúng mới được phát triển dựa trên một thuật toán ẩn mã sử dụng cách thay đổi khoảng cách giữa các dòng trong văn bản. Bài báo đưa ra một sơ đồ khối và mô tả thuật toán nhúng thông tin vào dữ liệu văn bản. Các thực nghiệm về khả năng nhúng và khả năng che giấu thông tin với tri giác thông thường của dữ liệu nhúng cũng được trình bày. Bài báo cũng nêu cách tiếp cận để trích xuất thông tin được nhúng từ các hình ảnh có chứa thủy vân bền vững. Bên cạnh đó, chúng tôi cũng đưa ra các giới hạn về khả năng ứng dụng của phương pháp dựa trên các thực nghiệm, các đánh giá về độ chính xác của việc trích xuất được dữ liệu và độ mạnh của phương pháp nhúng mới này đối với các phép biến đổi ảnh khác nhau. 

Automatic Classification of 2D Partial Discharge from Generator On-Line Measurement

2021 ◽  
Author(s):  
Claude Hudon ◽  
Melanie Levesque ◽  
Olivier Kokoko ◽  
Normand Amyot ◽  
Ryad Zemouri
Keyword(s):  
Partial Discharge ◽  
Automatic Classification ◽  
Line Measurement ◽  
On Line

A natural classification of Lasiosphaeria based on nuclear LSU rDNA sequences

2004 ◽  
Vol 108 (1) ◽  
pp. 26-34 ◽  
Author(s):  
Andrew N. Miller ◽  
Sabine M. Huhndorf
Keyword(s):  
Lsu Rdna ◽  
Natural Classification ◽  
Rdna Sequences

scholarly journals Multiresolution analysis of vibration signals acquired from locomotive Diesel engine for classification of engine states basing on signal statistical parameters

2017 ◽  
Vol 168 (1) ◽  
pp. 68-72
Author(s):  
Piotr BOGUŚ ◽  
Mateusz CIESZYŃSKI ◽  
Jerzy MERKISZ
Keyword(s):  
Diesel Engine ◽  
Complex Analysis ◽  
Statistical Parameters ◽  
Vibration Signals ◽  
Time Frequency ◽  
Significant Difference ◽  
Before And After ◽  
On Line ◽  
Locomotive Diesel

The paper presents a method of classification of locomotive Diesel engine states basing on vibration signals taken from an engine body and using chosen statistical parameters calculated for the original signal and it wavelet multiresolution components. The researches presented in the paper concern estimation of an engine states before and after a general repair. The target application of the presented researches is an on-line diagnostic system which can complement standard OBD systems. To this purpose the applied methods should not base on complex analysis of some spectral, time-frequency or scalogram plots but rather on choosing single diagnostic parameters which are suitable for the fast on-line diagnostic. The results have showed the significant difference in distinguishing of engine work before and after a general repair using some chosen statistical parameters applied to vibration signals.

scholarly journals Names of phytopathogenic fungi: a practical guide

2021 ◽  
Author(s):  
Pedro W Crous ◽  
Amy Y Rossman ◽  
Catherine Aime ◽  
Cavan Allen ◽  
Treena Burgess ◽  
...  
Keyword(s):  
Molecular Phylogeny ◽  
Classification System ◽  
Driving Force ◽  
Pathogenic Fungi ◽  
Phytopathogenic Fungi ◽  
Plant Pathogenic Fungi ◽  
Natural Classification ◽  
Online Databases ◽  
As Species

Names of phytopathogenic fungi and oomycetes are essential to communicate knowledge about species and their biology, control, and quarantine as well as for trade and research purposes. Many plant pathogenic fungi are pleomorphic, meaning that they produce different asexual (anamorph) and sexual (teleomorph) morphs in their lifecycles. Because of this, more than one name has been applied to different morphs of the same species, which has confused users of names. The onset of DNA technologies makes it possible to connect different morphs of the same species, resulting in a move to a more natural classification system for fungi, in which a single name for a genus as well as species can now be used. The move to a single nomenclature, as well as the advent of molecular phylogeny and the introduction of polythetic taxonomic approaches has been the main driving force for the re-classification of fungi, including pathogens. Nonetheless, finding the correct name for species remains challenging, but there is a series of steps or considerations that could greatly simplify this process, as outlined here. In addition to various online databases and resources, a list of accurate names is herewith provided of the accepted names of the most common genera and species of phytopathogenic fungi.

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