Near infrared reflectance (NIR) images of bruised `Delicious' applies were converted to images of texture properties. Bruises of two sizes (11 mm and 26 mm diameter) and two ages (1 d and 90 d) were examined. Seven texture properties (variance, entropy, product moment, difference entropy, inverse difference, difference variance, and sum variance) were computed from a cooccurrence matrix. Window size and neighborhood distance for the cooccurrence matrix were set to optimize the texture contrast between bruised and unbruised tissue. The window position was incrementally scanned over the entire apple image creating a new image of texture values. Four neighborhood directions (0 degree(s), 90 degree(s), 45 degree(s), 135 degree(s)) were considered. Sum variance was the only texture property that showed improved contrast of the bruised/unbruised areas relative to the original NIR image. All other texture properties produced images that highlighted the edge of the bruise. The variance property produced images with the best defined bruise edges irregardless of bruise size or age. Variance and sum variance show promise as additional features to the grey tone image for discriminating apple bruises.