Texture Feature Analysis of Milled Components Using Vision System

被引:0
|
作者
Shivanna, D. M. [1 ]
Kavitha, S. D.
Kiran, M. B. [1 ]
机构
[1] Dayananda Sagar Coll Engn, Dept Mech Engn, Bangalore, Karnataka, India
关键词
Surface Texture; Vision system; Surface Inspection; Texture features; Texture classification; ROUGHNESS;
D O I
10.4028/www.scientific.net/AMR.845.745
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Surface texture assessment is very useful in predicting the functional behaviour of engineering components. Surface texture is composed of three elements- roughness, waviness and form Error. The proposed method analyzes surface texture in two ways- Subjective analysis and Objective analysis. Subjective analysis makes use of histogram and texture spectrum whereas objective analysis uses Grey Level Co-occurrence Matrix (GLCM) based standard texture descriptors. Different milled surfaces having different textures are prepared by varying the machining parameters. The proposed method is non-contact in nature and high measuring speeds are possible. The method provides a complete texture description for a given surface.
引用
收藏
页码:745 / 749
页数:5
相关论文
共 50 条
  • [21] Texture analysis for grinding wheel wear assessment using machine vision
    Arunachalam, N.
    Ramamoorthy, B.
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 2007, 221 (03) : 419 - 430
  • [22] Texture analysis using feature-based pairwise interaction maps
    Chetverikov, D
    PATTERN RECOGNITION, 1999, 32 (03) : 487 - 502
  • [23] Colorization of Mountainous Landscape Images in Grayscale Using Texture Feature Analysis
    Kim, Ji Maan
    Zhang, Jane
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON VISION, IMAGE AND SIGNAL PROCESSING (ICVISP 2018), 2018,
  • [24] ANALYSIS OF HANDWRITTEN IMAGE USING FEATURE EXTRACTION ALGORITHM OF TEXTURE IMAGES
    Pandian, K. K. Soundra
    Mathivanan, P.
    Ganesamoorthy, B.
    2011 3RD INTERNATIONAL CONFERENCE ON COMPUTER TECHNOLOGY AND DEVELOPMENT (ICCTD 2011), VOL 1, 2012, : 467 - 471
  • [25] Classification of Breast Cancer Histopathology Images using Texture Feature Analysis
    Belsare, A. D.
    Mushrif, M. M.
    Pangarkar, M. A.
    Meshram, N.
    TENCON 2015 - 2015 IEEE REGION 10 CONFERENCE, 2015,
  • [26] Global vision system: Using hue thresholds to exact feature and recognize
    Xiong, Rong
    Chu, Jian
    2001, Harbin Institute of Technology (08)
  • [27] A global vision system: using hue thresholds to exact feature and recognize
    熊蓉
    褚健
    Journal of Harbin Institute of Technology, 2001, (03) : 233 - 238
  • [28] Computer Vision System for Expressing Texture Using Sound-Symbolic Words
    Yamagata, Koichi
    Kwon, Jinhwan
    Kawashima, Takuya
    Shimoda, Wataru
    Sakamoto, Maki
    FRONTIERS IN PSYCHOLOGY, 2021, 12
  • [29] Using spectrum to extract texture feature
    Xiao, ZT
    Yu, M
    Guo, CM
    2002 3RD INTERNATIONAL SYMPOSIUM ON ELECTROMAGNETIC COMPATIBILITY, 2002, : 657 - 659
  • [30] MULTI-FEATURE STEREO VISION SYSTEM FOR ROAD TRAFFIC ANALYSIS
    Houben, Quentin
    Diaz, Juan Carlos Tocino
    Warzee, Nadine
    Debeir, Olivier
    Czyz, Jacek
    VISAPP 2009: PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON COMPUTER VISION THEORY AND APPLICATIONS, VOL 2, 2009, : 554 - +