Clustering Boundary Points Detection Algorithm Based on Gradient Binarization

2012 ◽  
Vol 263-266 ◽  
pp. 2358-2363
Author(s):  
Yu Zhen He ◽  
Chun Hong Wang ◽  
Bao Zhi Qiu
Keyword(s):  
Data Processing ◽  
Boundary Point ◽  
Detection Algorithm ◽  
Experimental Results ◽  
Grid Technology ◽  
Gradient Operator ◽  
Boundary Points ◽  
Cluster Boundary ◽  
Novel Algorithm

In order to detect the boundary points of clustering efficiently, we proposed a novel algorithm which combined grid technology and gradient operator. In this algorithm the grid technology is used to enhance the speed of the data processing, and Prewitt gradient operator is applied to calculate gradient in 3×3 grid region from eight directions, the maximum being the central grid gradient. The gradient is used to judge whether the grid is the boundary grid or not, and a point in the boundary grid is a boundary point. Putting the method of image boundary processing into the practice of processing cluster boundary is a fresh idea for the research on cluster boundary. The experimental results indicate that this algorithm can effectively detect boundary of clusters in datasets with noises/outliers and have high running efficiency.

Developing an Inkjet Printer I: RGB Image to CMY Ink Amounts - Image Processing and Color Management

2020 ◽  
Vol 2020 (15) ◽  
pp. 350-1-350-10
Author(s):  
Yin Wang ◽  
Baekdu Choi ◽  
Davi He ◽  
Zillion Lin ◽  
George Chiu ◽  
...  
Keyword(s):  
Image Processing ◽  
Low Cost ◽  
Experimental Results ◽  
Color Management ◽  
Finger Nail ◽  
Inkjet Printer ◽  
Rgb Image ◽  
Novel Algorithm

In this paper, we will introduce a novel low-cost, small size, portable nail printer. The usage of this system is to print any desired pattern on a finger nail in just a few minutes. The detailed pre-processing procedures will be described in this paper. These include image processing to find the correct printing zone, and color management to match the patterns’ color. In each phase, a novel algorithm will be introduced to refine the result. The paper will state the mathematical principles behind each phase, and show the experimental results, which illustrate the algorithms’ capabilities to handle the task.

scholarly journals Distributed Beacon Drifting Detection for Localization in Unstable Environments

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Ming Xia ◽  
Peiliang Sun ◽  
Xiaoyan Wang ◽  
Yan Jin ◽  
Qingzhang Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Detection Algorithm ◽  
Experimental Results ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Location Information ◽  
Detection Accuracy ◽  
Research Issue ◽  
Fundamental Research

Localization is a fundamental research issue in wireless sensor networks (WSNs). In most existing localization schemes, several beacons are used to determine the locations of sensor nodes. These localization mechanisms are frequently based on an assumption that the locations of beacons are known. Nevertheless, for many WSN systems deployed in unstable environments, beacons may be moved unexpectedly; that is, beacons are drifting, and their location information will no longer be reliable. As a result, the accuracy of localization will be greatly affected. In this paper, we propose a distributed beacon drifting detection algorithm to locate those accidentally moved beacons. In the proposed algorithm, we designed both beacon self-scoring and beacon-to-beacon negotiation mechanisms to improve detection accuracy while keeping the algorithm lightweight. Experimental results show that the algorithm achieves its designed goals.

Moving Target Detection Based on Principle of Connectivity and Texture Gradient

2012 ◽  
Vol 605-607 ◽  
pp. 2117-2120
Author(s):  
Min Huang ◽  
Yang Zhang ◽  
Gang Chen ◽  
Guo Feng Yang
Keyword(s):  
Target Detection ◽  
Detection Algorithm ◽  
Experimental Results ◽  
Texture Gradient ◽  
Moving Target ◽  
Moving Target Detection ◽  
Gradient Information ◽  
Target Segmentation ◽  
Target Profile

In target detection, “hole” phenomenon is present in the detection result, and the shadow is difficult to remove. To solve these problems, we propose a target detection algorithm based on principle of connectivity and texture gradient. Firstly, we use the connectivity principle to find the largest target prospects connection area to get a complete target contour, secondly we use target texture gradient information to further remove the shadow of the target. At last, the experimental results show that the algorithm can obtain a clear target profile and improve the accuracy of the moving target segmentation.

Application of Immune Genetic Algorithm in Survey Data Processing

2012 ◽  
Vol 241-244 ◽  
pp. 1737-1740
Author(s):  
Wei Chen
Keyword(s):  
Genetic Algorithm ◽  
Immune System ◽  
Data Processing ◽  
Survey Data ◽  
Heuristic Algorithm ◽  
Experimental Results ◽  
Immune Genetic Algorithm ◽  
Basic Principles ◽  
Immune Operator ◽  
Biological Immune System

The immune genetic algorithm is a kind of heuristic algorithm which simulates the biological immune system and introduces the genetic operator to its immune operator. Conquering the inherent defects of genetic algorithm that the convergence direction can not be easily controlled so as to result in the prematureness；it is characterized by a better global search and memory ability. The basic principles and solving steps of the immune genetic algorithm are briefly introduced in this paper. The immune genetic algorithm is applied to the survey data processing and experimental results show that this method can be practicably and effectively applied to the survey data processing.

scholarly journals SPATIAL OUTLIERS DETECTION ALGORITHM (SODA) APPLIED TO MULTIBEAM BATHYMETRIC DATA PROCESSING

2019 ◽  
Vol 25 (4) ◽  
Author(s):  
Italo Oliveira Ferreira ◽  
Afonso de Paula dos Santos ◽  
Júlio César de Oliveira ◽  
Nilcilene das Graças Medeiros ◽  
Paulo César Emiliano
Keyword(s):  
Data Processing ◽  
Detection Algorithm ◽  
Bathymetric Data ◽  
Outliers Detection ◽  
Spatial Outliers

scholarly journals Handwritten tifinagh character recognition using simple geometric shapes and graphs

2019 ◽  
Vol 13 (2) ◽  
pp. 598
Author(s):  
Youssef Ouadid ◽  
Abderrahmane Elbalaoui ◽  
Mehdi Boutaounte ◽  
Mohamed Fakir ◽  
Brahim Minaoui
Keyword(s):  
Character Recognition ◽  
Graph Matching ◽  
Recognition Rate ◽  
Recognition System ◽  
Features Extraction ◽  
Experimental Results ◽  
Feature Points ◽  
Matching Method ◽  
Extraction Algorithm ◽  
Novel Algorithm

<p>In this paper, a graph based handwritten Tifinagh character recognition system is presented. In preprocessing Zhang Suen algorithm is enhanced. In features extraction, a novel key point extraction algorithm is presented. Images are then represented by adjacency matrices defining graphs where nodes represent feature points extracted by a novel algorithm. These graphs are classified using a graph matching method. Experimental results are obtained using two databases to test the effectiveness. The system shows good results in terms of recognition rate.</p>

Novel Algorithmic Approach to Deciphering Rovash Inscriptions

2015 ◽  
pp. 7222-7233 ◽  
Author(s):  
Loránd Lehel Tóth ◽  
Raymond Pardede ◽  
Gábor Hosszú
Keyword(s):  
Experimental Results ◽  
The Novel ◽  
Statistical Probability ◽  
Algorithmic Approach ◽  
Topological Parameters ◽  
Novel Method ◽  
Novel Algorithm

The article presents a method to decipher Rovash inscriptions made by the Szekelys in the 15th-18th centuries. The difficulty of the deciphering work is that a large portion of the Rovash inscriptions contains incomplete words, calligraphic glyphs or grapheme errors. Based on the topological parameters of the undeciphered symbols registered in the database, the presented novel algorithm estimates the meaning of the inscriptions by the matching accuracies of the recognized graphemes and gives a statistical probability for deciphering. The developed algorithm was implemented in software, which also contains a built-in dictionary. Based on the dictionary, the novel method takes into account the context in identifying the meaning of the inscription. The proposed algorithm offers one or more words in a different random values as a result, from which users can select the relevant one. The article also presents experimental results, which demonstrate the efficiency of method.

Company Acquisition Relations Extraction From Web Pages

2019 ◽  
pp. 1-17
Author(s):  
Jie Zhao ◽  
Jianfei Wang ◽  
Jia Yang ◽  
Peiquan Jin
Keyword(s):  
Relation Extraction ◽  
Experimental Results ◽  
Web Pages ◽  
Web Content ◽  
A Company ◽  
Novel Algorithm

In this chapter, we study the problem of extracting company acquisition relation from huge amounts of webpages, and propose a novel algorithm for a company acquisition relation extraction. Our algorithm considers the tense feature of Web content and classification technology of semantic strength when extracting company acquisition relation from webpages. It first determines the tense of each sentence in a webpage, where a CRF model is employed. Then, the tense of sentences is applied to sentences classification so as to evaluate the semantic strength of the candidate sentences in describing company acquisition relation. After that, we rank the candidate acquisition relations and return the top-k company acquisition relation. We run experiments on 6144 pages crawled through Google, and measure the performance of our algorithm under different metrics. The experimental results show that our algorithm is effective in determining the tense of sentences as well as the company acquisition relation.

scholarly journals Basketball Action Data Processing Method Based on Mode Symmetric Algorithm

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 560 ◽  
Author(s):  
Fei Zhang ◽  
Yi Jiang
Keyword(s):  
Data Processing ◽  
High Efficiency ◽  
Least Squares Method ◽  
Detection Algorithm ◽  
Processing Method ◽  
Target Image ◽  
Modal Data ◽  
Motion Data ◽  
Mode Decomposition ◽  
Data Processing Method

In the course of basketball training, a large number of basketball action data are generated according to the athletes’ body movements. Due to the low precision of the basketball action data processed by the traditional method in basketball technical training, basketball action processing is not in place. The basketball motion data processing method, based on the mode symmetric algorithm was studied. The basketball motion detection algorithm based on symmetric difference and background reduction was used to remove the background influence of basketball movement and obtain the binary basketball action target image containing the data. On this basis, the pole symmetric mode decomposition (ESMD) method was used to modally decompose the binary basketball action target image containing the data, and the least squares method was used to optimize the elliptic (AGM) curve to realize the screening of basketball action modal data. Through the cleaning and integration of basketball action modal data, integration and data reduction basketball action modal data, the data was processed efficiently. The experimental results showed that the proposed method was a high precision and high efficiency basketball action data processing method.

Extracting Top-k Company Acquisition Relations From the Web

2017 ◽  
Vol 13 (4) ◽  
pp. 27-41 ◽  
Author(s):  
Jie Zhao ◽  
Jianfei Wang ◽  
Jia Yang ◽  
Peiquan Jin
Keyword(s):  
Rapid Development ◽  
Relation Extraction ◽  
Experimental Results ◽  
Competitive Intelligence ◽  
Web Pages ◽  
Web Content ◽  
Web Page ◽  
Competitive Strategies ◽  
The Web ◽  
Novel Algorithm

Company acquisition relation reflects a company's development intent and competitive strategies, which is an important type of enterprise competitive intelligence. In the traditional environment, the acquisition of competitive intelligence mainly relies on newspapers, internal reports, and so on, but the rapid development of the Web introduces a new way to extract company acquisition relation. In this paper, the authors study the problem of extracting company acquisition relation from huge amounts of Web pages, and propose a novel algorithm for company acquisition relation extraction. The authors' algorithm considers the tense feature of Web content and classification technology of semantic strength when extracting company acquisition relation from Web pages. It first determines the tense of each sentence in a Web page, which is then applied in sentences classification so as to evaluate the semantic strength of the candidate sentences in describing company acquisition relation. After that, the authors rank the candidate acquisition relations and return the top-k company acquisition relation. They run experiments on 6144 pages crawled through Google, and measure the performance of their algorithm under different metrics. The experimental results show that the algorithm is effective in determining the tense of sentences as well as the company acquisition relation.

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