A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Learning in Adaptive Processing of Data Structures
Neural Processing Letters
A fuzzy neural network approach to machine condition monitoring
Computers and Industrial Engineering - Special issue: Selected papers from the 25th international conference on computers & industrial engineering in New Orleans, Louisiana
Applications of neural networks for grading textile yarns
Neural Computing and Applications
Genetic Evolution Processing of Classification
IEEE Transactions on Knowledge and Data Engineering
Attention-driven image interpretation with application to image retrieval
Pattern Recognition
Fast learning in networks of locally-tuned processing units
Neural Computation
An efficient algorithm for attention-driven image interpretation from segments
Pattern Recognition
Defects Identification in Textile by Means of Artificial Neural Networks
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
A hybrid model using genetic algorithm and neural network for classifying garment defects
Expert Systems with Applications: An International Journal
Stitching defect detection and classification using wavelet transform and BP neural network
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Finding out general tendencies in speckle noise reduction in ultrasound images
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A GA methodology for the scheduling of yarn-dyed textile production
Expert Systems with Applications: An International Journal
Classıfıcation of sleep apnea by using wavelet transform and artificial neural networks
Expert Systems with Applications: An International Journal
Nonwoven uniformity identification using wavelet texture analysis and LVQ neural network
Expert Systems with Applications: An International Journal
Incremental adaptation of fuzzy ARTMAP neural networks for video-based face classification
CISDA'09 Proceedings of the Second IEEE international conference on Computational intelligence for security and defense applications
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Statistical texture characterization from discrete wavelet representations
IEEE Transactions on Image Processing
Image denoising using scale mixtures of Gaussians in the wavelet domain
IEEE Transactions on Image Processing
A New SURE Approach to Image Denoising: Interscale Orthonormal Wavelet Thresholding
IEEE Transactions on Image Processing
Texture analysis and classification with tree-structured wavelet transform
IEEE Transactions on Image Processing
Automatic classification of granite tiles through colour and texture features
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Yarn periodical errors determination using three signal processing approaches
Digital Signal Processing
Hi-index | 12.06 |
The evaluation of yarn surface appearance is an important routine in assessing yarn quality in textile industry. Traditionally, this evaluation is subjectively carried out by manual inspection, which is much skill-oriented, judgmental and inconsistent. To resolve the drawbacks of the manual method, an integrated intelligent characterization and evaluation model is proposed in this paper for the evaluation of yarn surface appearance. In the proposed model, attention-driven fault detection, wavelet texture analysis and statistical measurement are developed and incorporated to fully extract the characteristic features of yarn surface appearance from images and a fuzzy ARTMAP neural network is employed to classify and grade yarn surface qualities based on the extracted features. Experimental results on a database of 576yarn images show the proposed intelligent evaluation system achieves a satisfactory performance both for the individual yarn category and global yarn database. In addition, a comparative study among the fuzzy ARTMAP, Back-Propagation (BP) neural network, and Support Vector Machine (SVM) shows the superior capacity of the proposed fuzzy ARTMAP in classifying yarn surface qualities of the database.