Results 141 to 150 of about 2,828 (179)
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Attributes Reduction Applied to Leather Defects Classification

2010 23rd SIBGRAPI Conference on Graphics, Patterns and Images, 2010
This paper presents a study on attributes reduction, comparing five discriminant analysis techniques: FisherFace, CLDA, DLDA, YLDA and KLDA. Attributes reduction has been applied to the problem of leather defect classification using four different classifiers: C4.5, kNN, Na\"{i}ve Bayes and Support Vector Machines. The results of several experiments on
Hemerson Pistori   +1 more
exaly   +2 more sources

Vision based leather defect detection: a survey

Multimedia Tools and Applications, 2022
Geetha S   +2 more
exaly   +2 more sources

Automatic recognition and defect compensation for calf leather

International Journal of Information Technology and Management, 2020
Chung Yeh
exaly   +2 more sources

Identification of surface leather defects

Proceedings of the 4th international conference conference on Computer systems and technologies e-Learning - CompSysTech '03, 2003
In this paper is discussing application of χ2 - criteria for analysis of leathers based on image histograms. It is proposed a manner determining standard histograms and basic evaluation, It is designed an algorithm of leather defects identification for surfaces analysis.
Lidiya Georgieva   +2 more
openaire   +1 more source

A Robust Real-time Leather Defect Segmentation Using YOLO

2023 18th Iberian Conference on Information Systems and Technologies (CISTI), 2023
Natural leather is a product made from animal skin which is treated through chemical procedure to preserve it. It is used in the manufacture of clothing, bags, furniture, automobile material, among others. Because of its capital value in industry, it is important to ensure its quality.
Silva, Vitor   +5 more
openaire   +2 more sources

Defect detection on leather by oriented singularities

1997
This paper presents a system for leather inspection based upon visual textural properties of the material surface. Defects are isolated from the complex and not homogeneous background by analyzing their strongly oriented structure. The patterns to be analyzed are represented in an appropriate parameter space using an optimization approach: in this way ...
Antonella Branca   +3 more
openaire   +1 more source

Automated defect inspection and classification of leather fabric

Intelligent Data Analysis, 2001
This paper describes an automated vision system for detecting and classifying surface defects on leather fabric. In the defect inspection process, visual defects are located and reported through a two-step segmentation procedure based on thresholding and morphological processing.
Choonjong Kwak   +2 more
openaire   +2 more sources

Quality Control Using U-Net: Detecting Defects in Leather

2023 18th Iberian Conference on Information Systems and Technologies (CISTI), 2023
Recently, there has been a significant amount of attention towards computer vision algorithms, particularly those that focus on semantic segmentation applications. This is due to the availability of big data to train models, as well as the computational ability of these algorithms.
Allahdad, Mehrab Khazraeiniay   +5 more
openaire   +2 more sources

Leather features selection for defects' recognition using fuzzy logic

Proceedings of the 5th international conference on Computer systems and technologies - CompSysTech '04, 2004
In the present work are investigated 12 histogram and statistical features for analysis of leather surface images. A research of the features suitability for surface defects detection is done. For the image analysis was used the quadtree decomposition method - a technique that partitions an image into homogeneous blocks.
Kaloyan Krastev   +2 more
openaire   +1 more source

Leather defect classification and segmentation using deep learning architecture

International Journal of Computer Integrated Manufacturing, 2020
The defects on a leather surface may be caused by the poor material handling process during the production and manufacturing stages.
Sze-Teng Liong   +3 more
openaire   +1 more source

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