Gabor feature extraction for character recognition: comparison with gradient feature

2005 ◽  
Author(s):  
C.-L. Liu ◽  
M. Koga ◽  
H. Fujisawa
Keyword(s):  
Feature Extraction ◽  
Character Recognition ◽  
Gabor Feature ◽  
Gabor Feature Extraction ◽  
Gradient Feature

Accelerating Multiresolution Gabor Feature Extraction for Real Time Vision Applications

2014 ◽  
Vol 76 (2) ◽  
pp. 149-168 ◽  
Author(s):  
Yong Cheol Peter Cho ◽  
Nandhini Chandramoorthy ◽  
Kevin M. Irick ◽  
Vijaykrishnan Narayanan
Keyword(s):  
Feature Extraction ◽  
Real Time ◽  
Gabor Feature ◽  
Gabor Feature Extraction

scholarly journals Handwritten English Character Recognition and translate English to Devnagari Words

2019 ◽  
pp. 142-151
Author(s):  
Shivali Parkhedkar ◽  
Shaveri Vairagade ◽  
Vishakha Sakharkar ◽  
Bharti Khurpe ◽  
Arpita Pikalmunde ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Feature Extraction ◽  
Character Recognition ◽  
Computational Time ◽  
Feature Vectors ◽  
Form Processing ◽  
Knn Classifier ◽  
Gabor Feature ◽  
Handwritten Document ◽  
The Individual

In our proposed work we will accept the challenges of recognizing the words and we will work to win the challenge. The handwritten document is scanned using a scanner. The image of the scanned document is processed victimization the program. Each character in the word is isolated. Then the individual isolated character is subjected to “Feature Extraction” by the Gabor Feature. Extracted features are passed through KNN classifier. Finally we get the Recognized word. Character recognition is a process by which computer recognizes handwritten characters and turns them into a format which a user can understand. Computer primarily based pattern recognition may be a method that involves many sub process. In today’s surroundings character recognition has gained ton of concentration with in the field of pattern recognition. Handwritten character recognition is beneficial in cheque process in banks, form processing systems and many more. Character recognition is one in all the favored and difficult space in analysis. In future, character recognition creates paperless environment. The novelty of this approach is to achieve better accuracy, reduced computational time for recognition of handwritten characters. The proposed method extracts the geometric features of the character contour. These features are based on the basic line types that forms the character skeleton. The system offers a feature vector as its output. The feature vectors so generated from a training set, were then used to train a pattern recognition engine based on Neural Networks so that the system can be benchmarked. The algorithm proposed concentrates on the same. It extracts totally different line varieties that forms a specific character. It conjointly also concentrates on the point options of constant. The feature extraction technique explained was tested using a Neural Network which was trained with the feature vectors obtained from the proposed method.

3-D Gaussian–Gabor Feature Extraction and Selection for Hyperspectral Imagery Classification

2019 ◽  
Vol 57 (11) ◽  
pp. 8813-8826 ◽  
Author(s):  
Sen Jia ◽  
Jiayue Zhuang ◽  
Lin Deng ◽  
Jiasong Zhu ◽  
Meng Xu ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Hyperspectral Imagery ◽  
Feature Extraction And Selection ◽  
Gabor Feature ◽  
Selection For ◽  
Gabor Feature Extraction

scholarly journals Face Recognition Based on Gabor Feature Extraction Followed by FastICA and LDA

2021 ◽  
Vol 68 (2) ◽  
pp. 1637-1659
Author(s):  
Masoud Muhammed Hassan ◽  
Haval Ismael Hussein ◽  
Adel Sabry Eesa ◽  
Ramadhan J. Mstafa
Keyword(s):  
Feature Extraction ◽  
Face Recognition ◽  
Gabor Feature ◽  
Gabor Feature Extraction

scholarly journals Application of Gabor Image Recognition Technology in Intelligent Clothing Design

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Sujuan Qiao
Keyword(s):  
Feature Extraction ◽  
Image Feature ◽  
Design System ◽  
Clothing Design ◽  
Time Performance ◽  
Extraction Algorithm ◽  
Calculation Process ◽  
Gabor Feature ◽  
Gabor Feature Extraction ◽  
Intelligent Clothing

Aiming at the complex problem of image recognition feature extraction, this paper proposes an intelligent clothing design model based on parallel Gabor image feature extraction algorithm. Based on the intelligent parallel mode, the algorithm decomposes and merges the calculation process of the image Gabor transformation, decomposes the entire image Gabor feature extraction calculation process into a parallel part and a nonparallel part, and accelerates the parallel part by using multiple cores. The calculation results are then combined to achieve the purpose of multicore parallel acceleration of the entire calculation process. Secondly, based on the consideration of improving the real-time performance of the intelligent clothing design system, combined with the existing multicore environment, this paper uses the intelligent model to design and implement the image parallel Gabor feature extraction algorithm and uses image processing and analysis technology to analyze the visual elements of traditional clothing and identify and quantify to form a relatively complete clothing visual element evaluation system, which provides a basis for large-scale collection and automated evaluation of clothing visual effects, as well as clothing trend tracking and prediction. Experiments show that the algorithm can effectively shorten the calculation time of Gabor image feature extraction and can obtain a good speedup in a multicore environment. At the same time, it combines with a multiscale intelligent clothing classification algorithm, on the basis of the VS2008 platform, combined with OpenCV 2.0, designed and implemented an intelligent clothing design system, and conducted experiments and system tests. The experimental results show that the algorithm given in this paper can accurately segment fabric defects from the background, which proves that the detection algorithm has a good detection effect. Simulation results show that the algorithm proposed in this paper can more accurately identify the state of clothing features, and the real-time performance of intelligent clothing design in a multicore environment has been improved to a certain extent.

scholarly journals Three-dimensional Gabor feature extraction for hyperspectral imagery classification using a memetic framework

2015 ◽  
Vol 298 ◽  
pp. 274-287 ◽  
Author(s):  
Zexuan Zhu ◽  
Sen Jia ◽  
Shan He ◽  
Yiwen Sun ◽  
Zhen Ji ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Hyperspectral Imagery ◽  
Three Dimensional ◽  
Gabor Feature ◽  
Gabor Feature Extraction
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