초록 ▼

The method of producing a binary flaw-no flaw image of an object, including employing an ultrasonic data acquisition system to obtain data values f(i,j) which define a C-scan image (F) of the object, dividing the C-scan image (F) into a plurality of subimages (Gk for k=1,2, . . . ,K), determining re

The method of producing a binary flaw-no flaw image of an object, including employing an ultrasonic data acquisition system to obtain data values f(i,j) which define a C-scan image (F) of the object, dividing the C-scan image (F) into a plurality of subimages (Gk for k=1,2, . . . ,K), determining regional threshold levels y(k) for each of the plurality of subimages, using said regional threshold levels y(k) to determine pixel threshold levels t(i,j) for each pixel (i,j) of the image (F) by interpolation, and generating a binary flaw-no flaw image (B) by assigning binary values thereto based on a comparison between the pixel threshold levels t(i,j) and data values f(i,j), thereby providing a method which achieves a high probability of flaw detection and a low probability of false flaw indications.

대표청구항 ▼

A method of producing a binary image of an object, the image showing any regions of flaws in the object and any regions in the object without flaws, the method comprising the steps of: ultrasonically scanning an object with sound wave energy; detecting echo signals reflected from the object; determi

A method of producing a binary image of an object, the image showing any regions of flaws in the object and any regions in the object without flaws, the method comprising the steps of: ultrasonically scanning an object with sound wave energy; detecting echo signals reflected from the object; determining data values f(i,j) from said echo signals which define a C-scan image of the object scanned; dividing the C-scan image into a plurality of subimages (Gk) for k=1,2, . . . ,K, wherein each subimage includes regional data values g(i,j); calculating an initial region value for each subimage from the regional data values g(i,j) of each subimage, the calculation of the initial regional value includes determining a maximum data value of the regional data value g(i,j) of each subimage, and using the maximum data value as the initial regional value for each subimage, respectively; using the initial regional values to dynamically determine regional threshold levels y(k) for each of the plurality of subimages, the regional threshold levels for each of the plurality of subimages being dependent on regional threshold levels in adjacent subimages, the regional threshold levels for each of the plurality of subimages determined from the initial region value in each subimage and initial region values in adjacent subimages, determining said regional threshold levels further includes determining said regional threshold levels as a function of at least one adjustment function which is defined based on characteristics of a data acquisition system used for ultrasonic scanning the object and detecting signals therefrom, determining said regional threshold levels for each subimage Gk further includes subtracting a regional threshold level y(k-1) from a first adjusted value derived from an adjustment function, to obtain a second adjusted value, operating on said second adjusted value by another adjustment function to obtain a third adjusted value, and adding said third adjusted value to. the regional threshold level y(k-1) to obtain the regional threshold level y(k); using said regional threshold levels y(k) to dynamically determine pixel threshold levels t(i,j) for each pixel (i,j) of said C-scan image, the pixel threshold levels being dependent on pixel threshold levels in adjacent subimages; comparing said pixel threshold levels t(i,j) to said data values f(i,j), respectively; assigning binary values to said compared data values, the binary values being indicative of flaws and non-flaws; and generating a binary image of the object, the image showing any regions of flaws in the object and any regions in the object without flaws.