scholarly journals Adaptive Video Caption Detection and Extraction Method Based on Color Filtering Principle

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Peng Ren ◽  
Genlin Zhao ◽  
Yongjun Liu
Keyword(s):  
Extraction Method ◽  
Experimental Results ◽  
Pixel Size ◽  
Filtering Algorithm ◽  
Adaptive Video ◽  
Color Video

Based on the principle of color (RGB) filtering, an improved adaptive video caption detection and extraction method is proposed. Firstly, the principle of the color filtering algorithm used in the video caption detection and extraction method is analyzed, and then the algorithm is improved adaptively according to the caption pixel size to filter the noise. Finally, experiments verify the effect of this method in extracting subtitles from video. The experimental results show that the accuracy of detecting and extracting subtitles in color video is as high as 99.3%.

Automatic term recognition based on statistics of compound nouns

Terminology ◽  
2000 ◽  
Vol 6 (2) ◽  
pp. 195-210 ◽  
Author(s):  
Hiroshi Nakagawa
Keyword(s):  
Experimental Evaluation ◽  
Extraction Method ◽  
Recognition Task ◽  
Experimental Results ◽  
Test Collection ◽  
Term Extraction ◽  
Academic Conference ◽  
Compound Nouns ◽  
Automatic Term Recognition ◽  
Technical Terms

The NTCIR1 TMREC group called for participation of the term recognition task which is a part of NTCIR1 held in 1999. As an activity of TMREC, they have provided us with the test collection of the term recognition task. The goal of this task is to automatically recognize and extract terms from the text corpus which consists of 1,870 abstracts gathered from the NACSIS Academic Conference Database. This article describes the term extraction method we have proposed to extract terms consisting of simple and compound nouns and the experimental evaluation of the proposed method with this NTCIR TMREC test collection. The basic idea of scoring a simple noun N of our term extraction method is to count how many nouns are conjoined with N to make compound nouns. Then we extend this score to measure the score of compound nouns because most of technical terms are compound nouns. Our method has a parameter to tune the degree of preference either for longer compound nouns or for shorter compound nouns. As for term candidates, in addition to noun sequences, we may add variations such as patterns of "A no B" that roughly means "B of A" or "A’ś B" and/or "A na B" where "A na" is an adjective. Experimental results of our method are promising, namely recall of 0.83, precision of 0.46 and F-value of 0.59 for exactly matched extracted terms when we take into account top scoring 16,000 extracted terms.

Wear Particles Recognition Based on Improved LBP

2013 ◽  
Vol 427-429 ◽  
pp. 1874-1878
Author(s):  
Guo De Wang ◽  
Zhi Sheng Jing ◽  
Guo Wei Qin ◽  
Shan Chao Tu
Keyword(s):  
Feature Extraction ◽  
Extraction Method ◽  
Local Binary Pattern ◽  
Recognition Accuracy ◽  
Binary Sequence ◽  
Texture Feature ◽  
Experimental Results ◽  
Wear Particles ◽  
Texture Feature Extraction ◽  
Feature Extraction Method

Wear particles recognition is a key link in the process of Ferrography analysis. Different kinds of wear particles vary greatly in texture, texture feature is one of the most important feature in wear particles recognition. Local Binary Pattern (LBP) is an efficient operator for texture description. The binary sequence of traditional LBP operator is obtained by the comparison between the gray value of the neighborhood and the gray value of the center pixel of the neighborhood, the comparison is too simple to cause the loss of the texture. In this paper, an improved LBP operator is presented for texture feature extraction and it is applied to the recognition of severe sliding particles, fatigue spall particles and laminar particles. The experimental results show that our method is an effective feature extraction method and obtains better recognition accuracy compared with other methods.

MODIFIED PRINCIPAL CURVES BASED FINGERPRINT MINUTIAE EXTRACTION AND PSEUDO MINUTIAE DETECTION

2011 ◽  
Vol 25 (08) ◽  
pp. 1243-1260 ◽  
Author(s):  
HONGYUN ZHANG ◽  
DUOQIAN MIAO ◽  
CAIMING ZHONG
Keyword(s):  
Extraction Method ◽  
Detection Method ◽  
Polygonal Line ◽  
Experimental Results ◽  
Data Sets ◽  
Gray Level ◽  
Principal Curves ◽  
Minutiae Extraction ◽  
Fingerprint Minutiae ◽  
Fingerprint Data

It is difficult but crucial for minutiae extraction and pseudo minutiae deletion of low quality fingerprint images in auto fingerprint identification systems. Traditional methods based on thinning images or gray-level images are, however, susceptible to noise. Reference 14 indicated that principal curves based fingerprint minutiae extraction was feasible to overcome the drawback, but the extended polygonal line (EPL) principal curves algorithm used in the paper extracted the principal curves ineffectively. As the fingerprint data sets are usually large, the original EPL principal curves algorithm is time-consuming. Meanwhile, scattered fingerprint data lead to the deviation of fingerprint skeleton. In this paper, the algorithm is modified, and a fingerprint minutiae extraction and pseudo minutiae detection method based on principal curves is proposed. Experimental results show that the modified EPL principal curves algorithm outperforms the original EPL algorithm both in efficiency and quality, and the proposed minutiae extraction method outperforms the methods proposed by Miao under noise conditions.

Extraction of Optimal Contour Dominant Points Based on ICT Images in Reverse Engineering

2013 ◽  
Vol 423-426 ◽  
pp. 2570-2575
Author(s):  
Guang Shuai Liu ◽  
Bai Lin Li
Keyword(s):  
Reverse Engineering ◽  
Extraction Method ◽  
Experimental Results ◽  
Ct Image ◽  
Redundant Data ◽  
Levels Of Detail ◽  
Dominant Points ◽  
Extraction Step ◽  
Optimal Contour ◽  
Industrial Ct

How to effectively extract contour dominant points is one of key problems in process of industrial CT image, second extraction method was put forward. Second extraction method included two steps: rough extraction and accurate extraction. Firstly, discrete circular curvatures of contour points are calculated. Secondly, through rough extraction step, bad points and points which arent correlated with contour features were removed. At last, through accurate extraction step, contour dominant points were extracted by levels of detail. Experimental results show that contour dominant points can describe contours shape and redundant data are removed, the proposed method is simple and efficient.

Research on Web Intelligent Information Extraction Method

2014 ◽  
Vol 539 ◽  
pp. 464-468
Author(s):  
Zhi Min Wang
Keyword(s):  
Information Extraction ◽  
Extraction Method ◽  
Experimental Results ◽  
Accurate Information ◽  
Web Page ◽  
Page Segmentation ◽  
Segmentation Technique ◽  
Ontology Extraction ◽  
Intelligent Information

The paper introduces segmentation ideas in the pretreatment process of web page. By page segmentation technique to extract the accurate information in the extract region, the region was processed to extract according to the rules of ontology extraction , and ultimately get the information you need. Through experiments on two real datasets and compare with related work, experimental results show that this method can achieve good extraction results.

Legal Judgment Elements Extraction Approach with Law Article-aware Mechanism

2022 ◽  
Vol 21 (3) ◽  
pp. 1-15
Author(s):  
Hu Zhang ◽  
Bangze Pan ◽  
Ru Li
Keyword(s):  
Text Classification ◽  
Extraction Method ◽  
State Of The Art ◽  
Recognition Task ◽  
Relevant Information ◽  
Experimental Results ◽  
Working Process ◽  
Legal Documents ◽  
Classification Framework ◽  
The Law

Legal judgment elements extraction (LJEE) aims to identify the different judgment features from the fact description in legal documents automatically, which helps to improve the accuracy and interpretability of the judgment results. In real court rulings, judges usually need to scan both the fact descriptions and the law articles repeatedly to find out the relevant information, and it is hard to acquire the key judgment features quickly, so legal judgment elements extraction is a crucial and challenging task for legal judgment prediction. However, most existing methods follow the text classification framework, which fails to model the attentive relations of the law articles and the legal judgment elements. To address this issue, we simulate the working process of human judges, and propose a legal judgment elements extraction method with a law article-aware mechanism, which captures the complex semantic correlations of the law article and the legal judgment elements. Experimental results show that our proposed method achieves significant improvements than other state-of-the-art baselines on the element recognition task dataset. Compared with the BERT-CNN model, the proposed “All labels Law Articles Embedding Model (ALEM)” improves the accuracy, recall, and F1 value by 0.5, 1.4 and 1.0, respectively.

Selectivity-Based Keyword Extraction Method

2016 ◽  
Vol 12 (3) ◽  
pp. 1-26 ◽  
Author(s):  
Slobodan Beliga ◽  
Ana Meštrović ◽  
Sanda Martinčić-Ipšić
Keyword(s):  
Extraction Method ◽  
Structural Information ◽  
Experimental Results ◽  
Linguistic Knowledge ◽  
Centrality Measures ◽  
Average Weight ◽  
Keyword Extraction ◽  
Source Text ◽  
Single Node ◽  
Node Centrality

In this work the authors propose a novel Selectivity-Based Keyword Extraction (SBKE) method, which extracts keywords from the source text represented as a network. The node selectivity value is calculated from a weighted network as the average weight distributed on the links of a single node and is used in the procedure of keyword candidate ranking and extraction. The authors show that selectivity-based keyword extraction slightly outperforms an extraction based on the standard centrality measures: in/out-degree, betweenness and closeness. Therefore, they include selectivity and its modification – generalized selectivity as node centrality measures in the SBKE method. Selectivity-based extraction does not require linguistic knowledge as it is derived purely from statistical and structural information of the network. The experimental results point out that selectivity-based keyword extraction has a great potential for the collection-oriented keyword extraction task.

A New Formant Detection Algorithm Based on Cepstrum

2011 ◽  
Vol 109 ◽  
pp. 681-684
Author(s):  
Jin Bao He ◽  
Hong Chao Fan ◽  
Xin Hua Yi ◽  
Jia Fen Hu
Keyword(s):  
Speech Signal ◽  
Traditional Method ◽  
Extraction Method ◽  
Detection Algorithm ◽  
Frequency Characteristics ◽  
Experimental Results ◽  
Frequency Resolution ◽  
Order Derivative ◽  
Formant Frequency ◽  
First Order

Formant frequency is one of important parameters for speech signal. This paper presents a new formant detection algorithm based on cepstrum. Firstly, the traditional speech formant method is discussed. To overcome the weakness of traditional method, an extraction method based on formant enhancement is described. Then, the first-order derivative of phase-frequency characteristics has better frequency resolution than logarithmic amplitude-frequency characteristics, so the first-order derivative of phase-frequency characteristics based on formant enhancement is proposed. Finally, the experimental results show that formants parameters can be extract more precisely.

scholarly journals Compact-MDD: Efficiently Filtering (s)MDD Constraints with Reversible Sparse Bit-sets

2018 ◽  
Author(s):  
Hélène Verhaeghe ◽  
Christophe Lecoutre ◽  
Pierre Schaus
Keyword(s):  
Data Structure ◽  
Practical Interest ◽  
Combinatorial Problems ◽  
Experimental Results ◽  
Decision Diagrams ◽  
Central Layer ◽  
Filtering Algorithm ◽  
Related Data ◽  
Bitwise Operations

Multi-Valued Decision Diagrams (MDDs) are instrumental in modeling combinatorial problems with Constraint Programming.In this paper, we propose a related data structure called sMDD (semi-MDD) where the central layer of the diagrams is non-deterministic.We show that it is easy and efficient to transform any table (set of tuples) into an sMDD.We also introduce a new filtering algorithm, called Compact-MDD, which is based on bitwise operations, and can be applied to both MDDs and sMDDs.Our experimental results show the practical interest of our approach, both in terms of compression and filtering speed.

Sign in / Sign up

Export Citation Format

Share Document