Conference Proceedings

International Conference on Advanced Computing, Communication and Networks - CCN 2011

Detection Of Foreign Fibers And Cotton Contaminants By using Intensity And Hue Properties



In view of the harm of cotton contaminants, the image processing method based on machine vision provides a good solution to eliminating the foreign fibers and contaminants. Digital image processing typically is executed by the special software programs that can manipulate the image in many ways. An automated cotton contamination detection system is economical and efficient to guarantee higher textile quality and lower production cost. There are various techniques used to detect the cotton contaminants and foreign fibers. The major contaminants found in cotton are plastic film, nylon straps, jute, dry cotton, bird feather, glass, paper, rust, oil grease, metal wires and various foreign fibers like silk, nylon, polypropylene of different colors and some of white color may or may not be of cotton itself. After analyzing cotton contaminants characteristics adequately, the paper presents various techniques for detection of white foreign fibers and contaminants from cotton. For machine vision system YCbCr color space has been implemented previously in which the performance parameters like speed of detection and time for detection need to be improved and also the problem of detection of white foreign fiber need to be consider, in this paper the detection has been carried out on HSI color space. By HSI we mean hue, saturation and intensity. It is more often to think about a color in terms of hue and saturation than in term of additive or subtractive components. Hue is the attribute of the visual sensation to one of the perceived colors; red, yellow, green and blue or combination of two of them. Intensity it is the total amount of light passing through a particular area. Saturation represents the purity of color. The HSI has been implemented on same platform as that of YCbCr color space and results has been compared on the basis of performance parameters like time for detection and no of targets detected, no of missed targets and no of false targets detected. The hardware used for the simulation are Processor: INTEL® core™ i3 CPU, Clock frequency: 2.27 GHz , RAM: 3 GB , Operating system: 32 bit, Hard disk: 320 Gb. The software used is the image processing tool box in MATLAB.

Conference Title : International Conference on Advanced Computing, Communication and Networks - CCN 2011
Conference Date(s) : June 2-3, 2011
Place : Hotel Aroma, Chandigarh, India
No fo Author(s) : 2
Page(s) : 861 - 871
Electronic ISBN :
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