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1、原文：Application Of Digital Image Processing In The Measurement Of Casting Surface RoughnessAhstract- This paper presents a surface image acquisition system based on digital image processing technology. The image acquired by CCD is pre-processed through the procedure of image editing, image equalizati

2、on, the image binary conversation and feature parameters extraction to achieve casting surface roughness measurement. The three-dimensional evaluation method is taken to obtain the evaluation parametersand the casting surface roughness based on feature parameters extraction. An automatic detection i

3、nterface of casting surface roughness based on MA TLAB is compiled which can provide a solid foundation for the online and fast detection of casting surface roughness based on image processing technology.Keywords-casting surface; roughness measurement; image processing; feature parameters.INTRODUCTI

4、ONNowadays the demand for the quality and surface roughness of machining is highly increased, and the machine vision inspection based on image processing has become one of the hotspot of measuring technology in mechanical industry due to their advantages such as non-contact, fast speed, suitable pre

5、cision, strong ability of anti-interference, etc 1,2. As there is no laws about the casting surface and the range of roughness is wide, detection parameters just related to highly direction can not meet the current requirements of the development of the photoelectric technology, horizontal spacing o

6、r roughness also requires a quantitative representation. Therefore, the three-dimensional evaluation system of the casting surface roughness is established as the goal 3,4, surface roughness measurement based on image processing technology is presented. Image preprocessing is deduced through the ima

7、ge enhancement processing, the image binary conversation. The three-dimensional roughness evaluation based on the feature parameters is performed . An automatic detection interface of casting surface roughness based on MA TLAB is compiled which provides a solid foundation for the online and fast det

8、ection of casting surface roughness.II. CASTING SURFACE IMAGE ACQUISITION SYSTEMThe acquisition system is composed of the sample carrier, microscope, CCD camera, image acquisition card and the computer. Sample carrier is used to place tested castings. According to the experimental requirements, we c

9、an select a fixed carrier and the sample location can be manually transformed, or select curing specimens and the position of the sampling stage can be changed. Figure 1 shows the whole processing procedure.,Firstly,the detected castings should be placed in the illuminated backgrounds as far as poss

10、ible, and then through regulating optical lens, setting the CCD camera resolution and exposure time, the pictures collected by CCD are saved to computer memory through the acquisition card. The image preprocessing and feature value extraction on casting surface based on corresponding software are fo

11、llowed. Finally the detecting result is output.III. CASTING SURFACE IMAGE PROCESSINGCasting surface image processing includes image editing, equalization processing, image enhancement and the image binary conversation,etc. The original and clipped images of the measured casting is given in Figure 2.

12、 In which a） presents the original image and b） shows the clipped image.A. Image EnhancementImage enhancement is a kind of processing method which can highlight certain image information according to some specific needs and weaken or remove some unwanted informations at the same time5.In order to ob

13、tain more clearly contour of the casting surface equalization processing of the image namely the correction of the image histogram should be pre-processed before image segmentation processing. Figure 3 shows the original grayscale image and equalization processing image and their histograms. As show

14、n in the figure, each gray level of the histogram has substantially the same pixel point and becomes more flat after gray equalization processing. The image appears more clearly after the correction and the contrast of the image is enhanced. Fig.2 Casting surface image Fig.3 Equalization processing

15、imageB. Image SegmentationImage segmentation is the process of pixel classification in essence. It is a very important technology by threshold classification. The optimal threshold is attained through the instmction thresh = graythresh （II）. Figure 4 shows the image of the binary conversation. The g

16、ray value of the black areas of the Image displays the portion of the contour less than the threshold （0.43137）, while the white area shows the gray value greater than the threshold. The shadows and shading emerge in the bright region may be caused by noise or surface depression.Fig4 Binary conversationIV. ROUGHNESS PARAMETER EXTRACTIONIn order to detect the surface roug