Optical hnaging/lmage Analysis System

The VIEEW™ (Video Image Enhanced Evaluation of Weathering) digital image analyzer, developed by Atlas Electric Devices Company, is an integration of digital image capturing and processing technologies (see Fig. 1). The system is capable of capturing digital images of samples under various lighting schemes optimized for the sample surface, of digitally processing the images to highlight and enhance surface defects, and of measuring and counting defects such that each sample is defined by a comprehensive statistical profile.

Initial applications of the VIEEW™ system were primarily focused on the evaluation of automotive exterior coatings defects, such as chipping, marring, and corrosion [1,2], but the technique can also be applied to the evaluation of the scratch resistance of molded and extruded plastics [3,4]. A first attempt at applying this new technique to the analysis of surface defects in weathered sealants has been undertaken with the objective of quantifying the degree of aging induced by various artificial accelerated laboratory and natural outdoor weathering schemes [5].

The system incorporates two different illumination methods: diffuse, chromatic (color) lighting for the detection of variations in chromatic contrast; and direct lighting to measure variations in geometric reflec­tion (gloss) and its textural characteristics.

Diffuse illumination is employed to accurately measure surface abnormalities resulting from chroma – ticity (color) difference. The sample is illuminated by a diffuse chromatic source where each color component—red, green and blue, or RGB—may be independently adjusted to maximize contrast on the sample surface.

Direct illumination is employed to provide the most accurate measurement of the reflectance, or gloss, of a surface, which also reveals surface irregularities such as scratches, chips, orange peel, etc. In direct illumination, the light strikes the sample normal (perpendicular) to its plane.

Two categories of surface defect analysis dominate the computerized image analysis: defect charac­terization and identification of surface texture properties. The former category includes defect size, shape, and distribution while the latter entails a determination of the change in surface appearance. The image analysis software exploits both binary (two-bit black and white) and gray scale image types to perform these characterizations.

Label

Type

Components

Crazing

(1-5)*

Dirt Pick Up

U~5)a

Chalking

(0-3)b

Visual Color Change (0-3)b

PU1-1

PU

1

3

1

3

1 (lighter)

PU2-3

PU

2

5

1

2

1 (lighter)

MS2-11

MS

2

3

3

0

1 (darker)

PS2-13

PS

2

2

5

0

3 (darker)

SR2-I7

SR

2

I

4

0

0

SR 1-20

SR

1

1

3

0

0

TABLE 1—Sample ratings based on visual inspection.

al: low/good, 5: high/poor b0: no/good, 3: high/poor