Texture is an important image feature in image analysis, which is related to quali-
tative properties of surfaces and corresponds to both brightness value and pixel locations.
Image texture has been introduced into a wide range of applications such as metal surface
analysis, textiles characterization, ultrasonic images processing, and food qualities evaluation.
One of the most common methods for texture analysis is the grey level co-occurrence matrix
(GLCM), which has a large number of texture features. In this work, an investigation of the
relationship between GLCM texture features and the cutting conditions in milling operations
(typically, feed, speed, and depth of cut) has been carried out. A vision system was employed to
capture images for specimens with various known cutting conditions; then, the images were
analysed by a software, which has been fully developed in-house to calculate 22 texture fea-
tures. The relationship between each texture feature and the three cutting conditions are dis-
cussed and the correlation coefficients are introduced. The results showed that 15 texture
features have good correlations with the feed, nine have good correlations with the speed, while
only two have good correlations with the depth of cut. |
