摘要
Corneal opacity is one of the most commonly used parameters for estimating postmortem interval （PMI）. This paper proposes a new method to study the relationship between changes of corneal opacity and PMI by processing and analyzing cornea images. Corneal regions were extracted from images of rabbits＇ eyes and described by color-based and texture-based features, which could represent the changes of cornea at different PMI. A KNN classifier was used to reveal the association of image features and PMI. The result of the classification showed that the new method was reliable and effective.
Corneal opacity is one of the most commonly used parameters for estimating postmortem interval （PMI）. This paper proposes a new method to study the relationship between changes of corneal opacity and PMI by processing and analyzing cornea images. Corneal regions were extracted from images of rabbits＇ eyes and described by color-based and texture-based features, which could represent the changes of cornea at different PMI. A KNN classifier was used to reveal the association of image features and PMI. The result of the classification showed that the new method was reliable and effective.
