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Study on Recent Research and Developments on Hairiness of Cotton Yarn by Image Processing Technique

R. Sudha, Dr. V. Chitraa

Abstract


Fibers protruding out from the main body of the yarn are called Yarn Hairiness. It is one of the main aspects, key indicator of limitation to detect the yarn quality. It affects the appearance of yarn and subsequent processing of textile process. It is in most circumstances an undesirable property, giving rise to problem of fabric production and also deteriorates the fabric appearance. Various developments regarding yarn hairiness have been described in the various researches. These researchers handle the various aspects such as hairiness measurement, modelling, simulation, spinning modifications and post spinning treatments to reduce hairiness and many techniques for detecting also. This study is an attempt to analytically review all significant recent growth and progresses regarding yarn hairiness, further possibilities of research and future work are also concisely discussed.


Keywords


Hairiness Measurement, Hairiness Modeling, Yarn Spinning, Image Processing, Yarn Hairiness, Segmentation

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References


Junfeng Jing, Mengying Huang, Pengfei Li And Xiaocui Ning - Automatic Measurement Of Yarn Hairiness Based On The Improved MRMRF Segmentation Algorithm The Journal Of The Textile Institute, 2017

Asis Patnaik -Studies On Reduction Of Yarn Hairiness Using Air Nozzles During Ring Spinning And Yarn Winding Department Of Textile Technology

Yinyin Sun, Zhongjian Li, Ruru Pan, Jian Zhou & Weidong - Measurement Of Long Yarn Hair Based On Hairiness Segmentation And Hairiness Tracking

GaoNoman Haleem1,2 and Xungai Wang2,3 - Recent research and developments on yarn hairiness Textile Research Journal published online 14 July 2014

Barella A. Yarn hairiness. Text Prog 1983; 13: 1–57.

Barella A. The hairiness of yarns. Text Prog 1993; 24: 1–46.

Barella A and Manich AM. Yarn hairiness update. Text Prog 1997; 26: 1–29.

Barella A and Manich AM. Yarn hairiness: a further update. Text Prog 2002; 31: 1–44.

Uster Technologies Ltd. Uster Tester 5 catalogue, 2011.

Uster Technologies Ltd. HL400 catalogue, 2011.

Behera BK. Image processing in textiles. Text Prog 2004; 35: 1–193.

Majumdar A. Soft computing in fibrous materials engineering. Text Prog 2011; 43: 1–95.

Jackowska-Strumillo L, Strzecha K, Grzelewski A, et al. Application of image processing methods for determination and analysis of yarn hairiness. In: Przetwarzanie i analiza obrazow w systemach wizji i sterowania. Automatics, AGH University of Science Publishing, Krakow, Poland: 2004.

Kuzan´ ski M and Jackowska-Strumillo L. The project of computer standing-system for yarn hairiness measurement. In: Conference on networks and informatics systems, Lodz, Poland, 2005.

Kuzan´ ski M and Jackowska-Strumillo L. Yarn hairiness determination by the use of image processing and analysis versus classical methods. In: Eighth international conference: the experience of designing and application of CAD systems in microelectronics, Lviv-Polyana, Ukraine, 2005.

Kuzan´ ski M. Measurement methods for yarn hairiness analysis - the idea and construction of research standing. In: Perspective technologies and methods in MEMS design, Lviv, Ukraine, 2006.

Kuzan´ ski M and Jackowska-Strumillo L. Yarn hairiness determination – the algorithms of computer measurement methods. In: Perspective technologies and methods in MEMS design, Lviv-Polyana, Ukraine, 2007.

Kuzan´ ski M, Fabijan´ ska A, Sankowski D, et al. Machine vision – automation of selected measurement systems. In: Perspective technologies and methods in MEMS design, Polyana, Ukraine, 2008.

Fabijan´ ska A, Kuzan´ ski M, Sankowski D, et al. Application of image processing and analysis in selected industrial computer vision systems. In: Perspective technologies and methods in MEMS design, Polyana, Ukraine, 2008.

Kuzan´ ski M. The algorithms of the yarn shape detection and calculation of the protruding fibres length. In: Perspective technologies and methods in MEMS design, Polyana, Ukraine, 2008.

Kuzan´ ski M and Jackowska-Strumillo L. Yarn hairiness determination – the algorithms of computer measurement methods In: Proceedings of perspective technologies and methods in MEMS design, Lviv-Polyana, Ukraine, 2007.

Ozkaya YA, Acar M and Jackson MR. Computer vision for yarn characterisation. In: Eighth United Kingdom mechatronics forum international conference, 2002.

Ozkaya YA, Acar M and Jackson MR. Digital image processing and illumination techniques for yarn characterization. J. Electron Imaging 2005; 14: 023001.

Ozkaya YA, Acar M and Jackson MR. Hair density distribution profile to evaluate yarn hairiness and its application to fabric simulations. J Text Inst 2007; 98:483–490.

Ozkaya YA, Acar M and Jackson MR. Simulation of photosensor-based hairiness measurement using digital image analysis. J Text Inst 2008; 99: 93–100.

Guha A, Amarnath C, Pateria S, et al. Measurement of yarn hairiness by digital image processing. J Text Inst 2009; 101: 214–222.

Fabijan´ ska A and Jackowska-Strumillo L. Image processing and analysis algorithms for yarn hairiness determination. Mach Vision Appl 2012; 23: 527–540.

Boykov YY and Jolly MP. Interactive graph cuts for optimal boundary and region segmentation of objects in N-D images. In: Proceedings of the eighth IEEE international conference on computer vision (ICCV 2001), Vancouver, Canada, 2001.

Chimeh MY, Tehran MA, Latifi M, et al. Characterizing bulkiness and hairiness of air-jet textured yarn using imaging techniques. J Text Inst 2005; 96: 251–255.

Wang XH, Wang JY, Zhang JL, et al. Study on the detection of yarn hairiness morphology based on image processing technique. In: Ninth international conference on machine learning and cybernetics, Qingdao, 2010.

Yuvaraj D and Nayar RC. A simple yarn hairiness measurement setup using image processing techniques. Indian J Fibre Text Res 2012; 37: 331–336.

Carvalho V, Cardoso P, Belsley M, et al. Determination of yarn hairiness using optical sensors. In: Eurosensors XX, Gothenburg, Sweden, 2006. Haleem and Wang 11 Downloaded from trj.sagepub.com at UNIV OF UTAH SALT LAKE CITY on November 28, 2014

Carvalho V, Cardoso P, Belsley M, et al. Development of a yarn evenness measurement and hairiness analysis system. In: 32nd annual conference on IEEE industrial electronics, Paris, 2006.

Carvalho VH, Cardoso PJ, Vasconcelos RM, et al. Optical yarn hairiness measurement system. In: 25th IEEE conference on industrial informatics, Vienna, 2007.

Carvalho V, Belsley M, Vasconcelos RM, et al. Yarn hairiness and diameter characterization using a CMOS line array. Measurement 2008; 41: 1077–1092.

Carvalho V, Cardoso P, Belsley M, et al. Yarn hairiness parameterization using a coherent signal processing technique. Sens Actuators A 2008; 142: 217–224.

Carvalho V, Soares F, Belsley M, et al. Automatic yarn characterization system. In: IEEE sensors, Lecce, 2008.

Carvalho V, Belsley M, Vasconcelos RM, et al. Yarn parameterization correlation using optical and capacitive sensors approaches. In: 35th Annual conference of IEEE industrial electronics, Porto, 2009.

Carvalho V, Soares F and Vasconcelos R. Artificial intelligence and image processing based techniques: a tool for yarns parameterization and fabrics prediction. In: IEEE conference on: Emerging technologies and factory automation, Mallorca, 2009.

Carvalho VH, Belsley MS, Vasconcelos RM, et al. Automatic yarn characterization system: design of a prototype. Sens J 2009; 9: 987–993.

Carvalho V, Belsley M, Vasconcelos R, et al. A comparison of mass parameters determination using capacitive and optical sensors. Sens Actuators A 2011; 167: 327–331.

Anand A, Chhaniwal VK and Narayanamurthy C. Hairiness measurement of textile yarns using crossed polarizers. Rev Sci Instrum 2005; 76: 076104.

Wang X. The effect of testing speed on the hairiness of ring-spun and sirospun yarns. J Text Inst 1997; 88: 99–106.

Wang X. Testing the hairiness of a rotor-spun yarn on the zweigle G565 hairiness meter at different speeds. J Text Inst 1998; 89: 167–169.

Wang X and Chang L. An experimental study of the effect of test speed on yarn hairiness. Text Res J 1999; 69: 25–29.

Wang X, Huang W and Huang X. Effect of test speed and twist level on the hairiness of worsted yarns. Text Res J 1999; 69: 889–892.

Keisokki. Hairiness-Diameter tester LST-V catalogue, 2011.

Lawson Hemphill Ltd. LH 483 catalogue, 2011.

SDL Atlas. Y103C portable hairiness tester catalogue, 2011.

Wang X. Measuring the hairiness of a rotor-spun yarn on the Uster tester 3 at different speeds. J Text Inst 1998; 89: 281–288.

Tang ZX, Wang X, Wang L and Fraser WB. The effect of yarn hairiness on air drag in ring spinning. Text Res J 2006; 76(7): 559–565.

Haleem N and Wang X. A comparative study on yarn hairiness results from manual test and two commercial hairiness meters. J Text Inst 2012: 104(5): 1–8.

Jackowska-Strumillo L, Jackowski T, Cyniak D, et al. Neural model of the spinning process for predicting selected properties of flax/cotton yarn blends. Fibres Text East Eur 2004; 12: 17–21.

Jackowska-Strumillo L, Cyniak D, Czekalski J, et al. Neural model of the spinning process dedicated to predicting properties of cotton–polyester blended yarns on the basis of the characteristics of feeding streams. Fibres Text East Eur 2008; 16: 28–36.

Beltran R, Wang L and Wang X. Predicting worsted spinning performance with an artificial neural network model. Text Res J 2004; 74: 757–763.

Baykal PD, Babaarslan O and Rizvan E. A statistical model for the hairiness of cotton/polyester blended OE rotor yarns. Fibres Text East Eur 2007; 15: 46–49.

U¨ reyen ME and Gu¨ rkan P. Comparison of artificial neural network and linear regression models for prediction of ring spun yarn properties. II. Prediction of yarn hairiness and unevenness. Fibers Polym 2008; 9:92–96.

Khan Z, Lim AEK, Wang L, et al. An artificial neural network-based hairiness prediction model for worsted wool yarns. Text Res J 2009; 79: 714–720.

Majumdar A, Majumdar PK and Sarkar B. An investigation on yarn engineering using artificial neural networks. J Text Inst 2006; 97: 429–434.

Majumdar A. Modeling of cotton yarn hairiness using adaptive neuro-fuzzy inference system. Indian J Fibre Text Res 2010; 35: 121–127.

Zhao B. Neural network for prediction of hairiness of ring spun cotton yarn. In: International conference on information technology, computer engineering and management sciences, Nanjing, Jiangsu, 2011.

Zhao B. Applications of artificial intelligence methods in the sizing hairiness of polyester/cotton blended yarn prediction. In: International conference on computer application and system modeling, Taiyuan, 2010.

Zhao B. Applying artificial neural network technique and theory to study the hairiness of polyester/cotton blended yarn in warping process. In: International conference on information technology, computer engineering and management sciences, Nanjing, 2011.

Arain F, Tanwari A, Hussain T, et al. Multiple response optimization of rotor yarn for strength, unevenness, hairiness and imperfections. Fibers Polym 2012; 13: 118–122.

Fattahi S, Taheri SM and Hosseini Ravandi SA. Cotton yarn engineering via fuzzy least squares regression. Fibers Polym 2012; 13: 390–396.

Haghighat E, Johari MS, Etrati SM, et al. Study of the hairiness of polyester–viscose blended yarn, part III. Predicting the yarn hairiness using artificial neural networks. Fibres Text East Eur 2012; 20: 90: 33–38. 12 Textile Research Journal 0(00) Downloaded from trj.sagepub.com at UNIV OF UTAH SALT LAKE CITY on November 28, 2014

Klein W. The technology of short staple spinning In: Manual of textile technology, short-staple spinning series. The Textile Institute, 1987.

Mirzaei M, Gharehaghaji AA and Zarrebini M. A new method of yarn hairiness reduction by air suction during carding. Text Res J 2012; 82: 2128–2136.

Wang X and Chang L. Reducing yarn hairiness with a modified yam path in worsted ring spinning. Text Res J 2003; 73: 327–332.

Thilagavathi G, Gukanathan G and Munusamy B. Yarn hairiness controlled by modified yarn path in cotton ring spinning. Indian J Fibre Text Res 2005; 30: 295–301.

Thilagavathi G, Udayakumar D, Sasikala L, et al. Yarn hairiness controlled by various left diagonal yarn path offsets by modified bottom roller flute blocks in ring spinning. Indian J Fibre Text Res 2009; 34: 328–332.

Wang X, Miao M and How Y. Studies of jetring spinning. Part I: Reducing yarn hairiness with the jetring. Text Res J 1997; 67: 253–258.

Najar SS, Khan ZA and Wang XG. The new Solo–Siro spun process for worsted yarns. J Text Inst 2006; 97: 205–210.

Sherafati Nejad A, Najar SS and Hasani H. Application of air-jet nozzle in short staple Siro spinning system. J Text Inst 2011; 102: 14–18.

Yılmaz D and Usal M. A study on siro-jet spinning system. Fibers Polym 2012; 13: 1359–1367.

Yilmaz D and Usal MR. Improvement in yarn hairiness by the siro-jet spinning method. Text Res J 2013; 83: 1081–1100.

Yilmaz D and Usal MR. A comparison of compact-jet, compact, and conventional ring-spun yarns. Text Res J 2011; 81: 459–470.

Feng J, Xu BG, Tao XM, et al. Theoretical study of a spinning triangle with its application in a modified ring spinning system. Text Res J 2010; 80: 1456–1464.

Alamdar-Yazdi A. Effects of directed movement of fibres in a twist triangle on yarn quality. J Text Inst 2011; 102: 263–271.

Haghighat E, JohariMand Etrati SM. Study of the hairiness of polyester–viscose blended yarns. Part II. Winding section parameters. Fibres Text East Eur 2008; 16: 68.

Qiu H, Zhang Y, Xu Z, et al. A novel method to reduce hairiness level of ring spun yarn. Fibers Polym 2012; 13: 104–109.

Xia Z, Xu W, Zhang M, et al. Reducing ring spun yarn hairiness via spinning with a contact surface. Fibers Polym 2012; 13: 670–674.

Aslam S, Lamb PR and Wang X. Improved incorporation of fibres for more abrasion resistant yarns. J Text Inst 2013; 104: 1221–1229.


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