scholarly journals Efficient extraction algorithm for local fuzzy features of dynamic images

2019 ◽  
Vol 12 (4-5) ◽  
pp. 1311-1325
Author(s):  
Yunsai Chen ◽  
◽  
Zhao Yang ◽  
Liang Ma ◽  
Peng Li ◽  
...  
Keyword(s):  
Extraction Algorithm ◽  
Fuzzy Features ◽  
Efficient Extraction

Fast Background Extracting Algorithms of Video Sequence Based on Invariance

2013 ◽  
Vol 443 ◽  
pp. 18-21
Author(s):  
Zhi Zheng Zhou ◽  
Shu Ming Jiang
Keyword(s):  
Real Time ◽  
Video Sequence ◽  
Video Stream ◽  
Computation Complexity ◽  
Fuzzy Similarity ◽  
Extraction Algorithm ◽  
Background Extraction ◽  
Traffic Environment ◽  
Efficient Extraction

In order to reduce the complexity and computation of the background extraction algorithm, this paper presents a new background extraction algorithm corresponding to the intelligent traffic environment based on the invariance of background. In the algorithm, we partition the background into sub-blocks, and compare the characteristics of the several continues frames in the video stream, then update the background block by fuzzy similarity processing in real time. The evaluation proves that the new algorithm can accomplish the higher efficient extraction with less computation complexity.

GESTURE RECOGNITION SYSTEM FOR NIGERIAN TRIBAL GREETING POSTURES USING SUPPORT VECTOR MACHINE

2020 ◽  
Vol 5 (2) ◽  
pp. 609
Author(s):  
Segun Aina ◽  
Kofoworola V. Sholesi ◽  
Aderonke R. Lawal ◽  
Samuel D. Okegbile ◽  
Adeniran I. Oluwaranti
Keyword(s):  
Support Vector Machine ◽  
Gesture Recognition ◽  
Recognition Rate ◽  
Recognition Task ◽  
Recognition System ◽  
Human Interaction ◽  
Support Vector ◽  
System A ◽  
Extraction Algorithm ◽  
Gaussian Blur

This paper presents the application of Gaussian blur filters and Support Vector Machine (SVM) techniques for greeting recognition among the Yoruba tribe of Nigeria. Existing efforts have considered different recognition gestures. However, tribal greeting postures or gestures recognition for the Nigerian geographical space has not been studied before. Some cultural gestures are not correctly identified by people of the same tribe, not to mention other people from different tribes, thereby posing a challenge of misinterpretation of meaning. Also, some cultural gestures are unknown to most people outside a tribe, which could also hinder human interaction; hence there is a need to automate the recognition of Nigerian tribal greeting gestures. This work hence develops a Gaussian Blur – SVM based system capable of recognizing the Yoruba tribe greeting postures for men and women. Videos of individuals performing various greeting gestures were collected and processed into image frames. The images were resized and a Gaussian blur filter was used to remove noise from them. This research used a moment-based feature extraction algorithm to extract shape features that were passed as input to SVM. SVM is exploited and trained to perform the greeting gesture recognition task to recognize two Nigerian tribe greeting postures. To confirm the robustness of the system, 20%, 25% and 30% of the dataset acquired from the preprocessed images were used to test the system. A recognition rate of 94% could be achieved when SVM is used, as shown by the result which invariably proves that the proposed method is efficient.

An Answer Extraction Algorithm Based on Syntax Structure Feature Parsing and Classification

2009 ◽  
Vol 31 (4) ◽  
pp. 662-676 ◽  
Author(s):  
Bao-Shun HU ◽  
Da-Ling WANG ◽  
Ge YU ◽  
Ting MA
Keyword(s):  
Structure Feature ◽  
Answer Extraction ◽  
Extraction Algorithm
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