	AYA-40VL uses Pentium lV processor and Windows as OS. This 10bit high performance Machine Vision System for a cooled line sensor camera.

		Camera(CL-5000): This 12 bit cooled line sensor camera captured slight contrast differences and output them as stable digital data.

		MIL original technique detects defects, shallow line, and light unevenness, even in low brightness environment.

	AYA-40VL real-time operation eliminates irregular illumination, shading, and emphasizes the defecive part of image automatically.

	Easy Data Management: The operator is able to easily save the defect image and the address information. For simpler system management, the AYA-40VLseries is equipped LAN connection.

AYA-40VL Ditection Examples

Gel and foreign object on the glass

a. Input image

There are not enough brightness changes to have the threshold.

b. Emphatic image

There are brightness differences with the glass surface, but still the lighting is uneven.

c. Special filtered image

This algorithm only emphasizes the defecive part and eliminates ligting uneveness and noise, by surface uneveness, to have threshold.

Chipped edge of the glass

a. Emphatic image

Showing the chipped edge as the black dots.

b. Special filtered image

This algorithm emphasizes the defecive part and eliminates ligting uneveness and noise, by surface uneveness, but still need to the inspection blind area on the edge.

c. Edge erasing image

The edge is erased but not the defective part and the surface and noise were smoothen, SN ratio is increased.

Crosswise streak on the glass

a. Emphatic image

There is the streak on perpendicular to the running direction.

b. Edge enhancing image

The streak is emphasized and the ligting uneveness and noise, by surface uneveness, are eliminated. Smoothing the depth to not to cause the detection accuracy variance even changing inspection objects.

c. Labeling image

The defect part are colored in red, which is filled with different colors by the size, the depth, and the numbers.

Don't you have a hard time to inspect those objects?

Application of Edge erasing 1: Missing edge of shaft or printed object

a.Emphatic image

The object have patterns on the surface

b. Neighboring Pixel Summation image

It might necessary to set the inspection blind spot or adding more camera because the edge is emphasized with defective part.

c. Edge erasing image

This function erases the edges of patterns to do real-time processing by one camera.

Application of Edge erasing2:
300 micron foreign object on convexo-concave surface plastic panel

a. Emphatic image

There are the lept asperities are all over the panel, the defect is overlapped with those.

b. Edge erasing image

Smoothen the surface in real-time and the brigtness waveform shows the defect.

c. Labeling image

The defective part is colored in red.