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.

A FOURIER-RADIAL DESCRIPTOR ALGORITHM FOR INVARIANT FEATURE EXTRACTION

2006 ◽  
Vol 04 (01) ◽  
pp. 197-212
Author(s):  
CHALLA S. SASTRY ◽  
ARUN K. PUJARI ◽  
B. L. DEEKSHATULU
Keyword(s):  
Feature Extraction ◽  
Extraction Method ◽  
Symmetric Functions ◽  
It Use ◽  
Feature Extraction Method ◽  
Invariant Feature ◽  
Feature Extraction Algorithm ◽  
Extraction Algorithm ◽  
Gabor Feature ◽  
Gabor Feature Extraction

By integrating the Fourier techniques and the edge information obtained using the radial symmetric functions, we propose in this paper an invariant feature extraction algorithm. Unlike the Gabor feature extraction method, the present method does not use direction dependent filters, nor does it use the images in polar form, for rotation invariance. Besides, the present Fourier-Radial invariant feature extraction algorithm, suitable for both the texture and non-texture images, has functional analogy with the Gabor feature extraction method, and hence, is easily implementable. It is mathematically proved, and justified through computations, that the method can generate the invariant and discriminative feature vectors. Our simulation results demonstrate that the method can be used for such applications as content-based image retrieval.

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

Tactile image computation using a feature extraction algorithm

Robotica ◽  
1992 ◽  
Vol 10 (3) ◽  
pp. 241-254
Author(s):  
M. Mehdian
Keyword(s):  
Feature Extraction ◽  
Local Property ◽  
Recognition System ◽  
Image Feature ◽  
Image Size ◽  
Feature Extraction Algorithm ◽  
Extraction Algorithm ◽  
Tactile Image ◽  
Feature Values ◽  
Image Computation

SUMMARYA binary tactile image feature extraction algorithm using image primitive notation and perceptrons is presented. The basic image segments are defined as geometric factors by which the image structure is described so that effective feature values such as image shape, image size, perimeter and texture may be extracted on the basis of local image computation. The local property of the tactile image computation is evaluated by the concept called order of the perceptrons and based on this feature extraction algorithm, an efficient tactile image recognition system is realised.

Study of Fingerprint Image Feature Extraction Algorithm

2014 ◽  
Vol 519-520 ◽  
pp. 577-580
Author(s):  
Shuai Yuan ◽  
Guo Yun Zhang ◽  
Jian Hui Wu ◽  
Long Yuan Guo
Keyword(s):  
Feature Extraction ◽  
Recognition System ◽  
Fingerprint Recognition ◽  
Image Feature ◽  
Feature Points ◽  
Orientation Field ◽  
Fingerprint Image ◽  
Image Feature Extraction ◽  
Feature Extraction Algorithm ◽  
Extraction Algorithm

Fingerprint image feature extraction is a critical step to fingerprint recognition system, which studies topological structure, mathematical model and extraction algorithm of fingerprint feature. This paper presents system design and realization of feature extraction algorithm for fingerprint image. On the basis of fingerprint skeleton image, feature points including ending points, bifurcation points and singular points are extracted at first. Then false feature points are detected and eliminated by the violent changes of ambient orientation field. True feature points are marked at last. Test result shows that the method presented has good accuracy, quick speed and strong robustness for realtime application.

scholarly journals Fusion Mode and Style Based on Artificial Intelligence and Clothing Design

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Jiali Qiu ◽  
Lianghua Ma
Keyword(s):  
Artificial Intelligence ◽  
Three Dimensional ◽  
Intelligent Manufacturing ◽  
Industrial Robots ◽  
Design System ◽  
Design Elements ◽  
Advantages And Disadvantages ◽  
Clothing Design ◽  
The Right ◽  
Intelligent Clothing

With the upgrading of intelligent manufacturing, industrial robots will play an important role in the garment industry. The purpose of this article was to study the pattern and style based on the integration of artificial intelligence and clothing design. In this article, the digital modeling of clothing design and the case analysis of intelligent clothing design are described using the method of comparative experiment. The experimental results are obtained from the analysis of fuzzy number of clothing design language evaluation, three-dimensional human body construction clothing size, clothing design elements and auxiliary functions, and the analysis of the advantages and disadvantages of clothing design system. The popular clothing sample is D4 (0.4862), which is 20% higher than other products. It can be concluded that the model proposed in this article can grasp the needs of consumers and select the right one according to the market positioning. The fabric mass production fashion brand can significantly improve the efficiency and satisfaction of the fabric selection decision-making process. It provides enough technical support and style model for intelligent clothing design.

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
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