The Computer Vision's Application In The Crack Detecting Of Glassware

In the production of glassware , with the enhancing of production speed and more and more strict request of quality , the traditional method detecting crack can not do well because of major factor. This method can not insure the quality and quantity of product. In this case , many factories begin to manufacture the machine that can detects the crack of glassware . The product those have been developed have some default , such as highly precision with machine manufacturing, uneasy adjusting and expensive price .With the development of computer software and hardware and perfecting of computer vision's theory .In foreign countries some factories has made out this kind of product. Its quality is good. Our country is studying this kind of product and has not make out any kind of finished product .The method for detecting crack with computer is becoming viable . Compare to the traditional product that is made with the way of mechanical touching, The machine according to this kind of method to product has virtues:Low manufacturing price and low precision to mechanical manufacturing ;High feasibility and easy adjusting ;The detecting speed of system can enhance with the increase of CPU speed.Low request to working environment.Crack Detecting System of glass bottles is a subsystem of on-line detecting system of glassware with computer envision . We cooperate with Guilin Glass Factory to develop this system . I have invented two new way in this kind of system . Easy judging method (EJM) and border feature judging method (BFJM).These ways all follow the principle of computer vision .First , choosing right camera , lighting and image card to get a series of digital image with special space that can show crack . System uses the reflect of crack to judge, and the crack location of bottle is not static. The crack may lies in each place of a bottle. In this system when a series of digital images are being gotten, the camera and the light source are static, but the glass bottle is swirling .The Second , this system does some kinds of pre-processing in user buffer memory . After pre-processing , in order to distinct the crack area (CA) and disturbing area (DA) system segment the image . Then system extracts features from each small area . Last I judge the glass bottle in judging method according to all kinds of parameters .EJM and BFJM both choose a same way to get digital image . In the phase of image preprocessing ,the former uses adjacent area average method (AAAM) to smooth noise , the latter uses median fitting method (MFM) to smooth noise .These two method smoothing effect the border of area differently .AAAM faints the border of a image . MFM can maintain the border of a Image not to distort .In the phase of segmenting a image ,EJM and BFJM both use the best threshold method (BTM) to segment images . In the EJM , facula area feature and facula location feature are extract to judge bottles . In the BFJM , Laplacian is used to detect the border basing BTM .then 1 extract the border of each area and calculate the chain code of the border . afterwardsthe thin degree and circle degree with Fourier are extracted to judge bottle .In the precondition of judging crack rightly .comparing to EJM , BFJM has low request to machine for detecting . but its processing speed is slow . The essence is sacrificing part of processing speed to exchange the low price and low precision .This system realizes detecting the crack of bottles with Visual C++ .