Needle-Stamped Digits on Metal

In this sample application, we present the possibilities opened by the template matching functionality added to NeuroCheck after version 4.0.

Needle-stamped characters are often used to mark on metal parts, because of their robustness. Unlike, for example, ink-jet characters they are very hard to remove again and easily survive subsequent manufacturing processes and the rough environmental conditions in metal-working factories. Unfortunately they are also hard to recognize for an image processing system, because they tend to disintegrate into single points instead of contiguous, unbroken lines.

There are two ways to solve this problem:

1.Use a morphological filter, erosion or opening in this case, to widen the individual needle-marks until the lines become unbroken. 

This approach causes several problems. First of all morphological filter processes tend to be quite time-consuming. Furthermore, as can be seen in the image below, the "2" and "3" in the above image will easily be fused together by the filtering process. Although NeuroCheck allows you to define highly specialized filter kernels adapted to the geometry of specific image structures, there would be a very difficult tradeoff between the requirements of the different structures appearing in characters.

2.Use template matching. It searches for objects within an image based on the similarity of image regions to predefined templates. You can easily define templates tailored to your application by presenting some typical images to NeuroCheck and indicating the template patterns using the mouse, as shown in the image below. NeuroCheck will then search for a specified number of patterns in the image exhibiting a minimum similarity to the defined templates.

Despite the obvious differences in the appearance of the digits, a single template per digit class proves to be sufficient to detect all digits reliably, as in the next image. Recognizing the precisely located digits is then no problem at all. 

Some of our clients include:

Agilent
Amatech
Anheuser Busch
Behr
BMW
Borg Warner
Bosch
Braun DaimlerChrysler
Delphi
EGO
Eaton
Festo
Ford
GeneScan
Getrag
Hema
INA
Intel
Jaguar
Johnson&Johnson
Kodak
Leuze
Motorola
Panasonic
Philips
Riwisa
Schaffner
Schott
Siemens
TRW Automotive
Tyco
ZF Lemforder