Identification of Textile Defects Based on GLCM and Neural Networks
نویسندگان
چکیده
منابع مشابه
Identification of Textile Defects Based on GLCM and Neural Networks
In modern textile industry, Tissue online Automatic Inspection (TAI) is becoming an attractive alternative to Human Vision Inspection (HVI). HVI needs a high level of attention nevertheless leading to low performance in terms of tissue inspection. Based on the co-occurrence matrix and its statistical features, as an approach for defects textile identification in the digital image, TAI can poten...
متن کاملDefects Identification in Textile by Means of Artificial Neural Networks
In this paper we use a neural network approach for defects identification in textile. The images analyzed came from an artificial vision system that we used to acquire and memorize them in bitmap file format. The vision system is made of two grey scale line scan camera arrays and each array is composed of four CCD cameras with a sensor of 2048 pixels. Every single camera has a field of view of ...
متن کاملNeural network based detection of local textile defects
A new approach for the segmentation of local textile defects using feed-forward neural network is presented. Every fabric defect alters the gray-level arrangement of neighboring pixels, and this change is used to segment the defects. The feature vector for every pixel is extracted from the gray-level arrangement of its neighboring pixels. Principal component analysis using singular value decomp...
متن کاملIdentification of Crack-like Defects Based on Methods of Magnetic Inspection and Neural Networks Technologies
The method of identification of cracks-like defects in coated pipes is proposed. A cross section of the pipe, reinforced by inner annular coat and the magnetic field propagation of permanent magnets modelled. The identification of several geometric parameters of defects is carried out. Investigated the influence of different geometric parameters of the defects on the performance of neural netwo...
متن کاملAircraft Visual Identification by Neural Networks
In the present paper, an efficient method for three dimensional aircraft pattern recognition is introduced. In this method, a set of simple area based features extracted from silhouette of aerial vehicles are used to recognize an aircraft type from its optical or infrared images taken by a CCD camera or a FLIR sensor. These images can be taken from any direction and distance relative to the fly...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Computer and Communications
سال: 2015
ISSN: 2327-5219,2327-5227
DOI: 10.4236/jcc.2015.312001