Gary F Nevers, Age 602 Ellen Rd, Lynn, MA 01904

5301129, Apr 5, 1994

Apr 29, 1992

7/875672

Stephen V. McKaughan - Arlington MA
Gary F. Nevers - Lynn MA
Joseph W. Landry - Saugus MA
John P. Fallon - Andover MA
Paul R. Adomaitis - Trafford PA

Aluminum Company of America - Pittsburgh PA

G06F 1100

364552

Method and apparatus for inspecting the surface of a moving web of homogeneous material for anomalies, the apparatus including a light source for illuminating the web surface and a light sensitive detector for receiving data from the web surface. The data is representative of the light reflected from the surface, as the light is affected by surface anomalies and background information. Computational means are provided for receiving output data from the detector in response to the data the detector receives from the web surface, and for processing the output data in a manner that determines the presence of surface anomalies. The computation means includes a plurality of filters for transforming the surface data in a manner that effects substantial elimination of the background information, and means for establishing threshold levels for background information. In addition, automatic means is provided for modifying the threshold levels in response to changes in the reflectance, frequency, or contrast of background information received by the detector and forwarded to the computation means.

5351308, Sep 27, 1994

Dec 6, 1993

8/163383

Jon J. Kaminer - Richmond VA
Gary F. Nevers - Lynn MA
Edgar V. Sellers - Wilmington NC

E. I. Du Pont de Nemours and Company - Wilmington DE

G06K 900

382 8

A method and apparatus to non-destructively inspect and quantify yarn crimp characteristics either off-line or on-line at speeds in excess of 2,000 yds. /min. by acquiring images of yarn crimp on-line during the manufacturing process, then digitizing the images of yarn crimp and performing all data processing from the digital data required. Each image is segregated into features (e. g. valid crimp, low frequency oscillations, high frequency oscillations, edge oscillations, and unconfirmed oscillations with each parameter being analyzed separately. Features are segmented two dimensionally using techniques such as, but not limited to, local max/min intensity profiles and spatial intensity and frequency thresholding. Regions identified as abnormal are separated from areas of valid crimp before determining crimp frequency. Outputs of individual analysis are combined to determine global tow quality.