Methods for pressure sore monitoring remain both a clinical and research challenge. Improved methodologies could assist physicians in developing prompt and effective pressure sore interventions. In this paper a technique is introduced for the assessment of pressure sores in guinea pigs

using captured color images. Sores were artificially induced

utilizing a system particularly developed for this purpose. Digital images were obtained from the suspicious region in days 3 and 7 post-pressure sore generation. Different segments of the color images were divided and labeled into three classes

based on their severity status. For quantitative analysis

a color based texture model

which is invariant against monotonic changes in illumination

is proposed. The texture model has been developed based on the local binary pattern operator. Tissue segments were classified

using the texture model and its features as inputs to a combination of neural networks. Our method is capable of discriminating tissue segments in different stages of pressure sore generation

and therefore can be a feasible tool for the early assessment of pressure sores.