Mapayi Temitope, Viriri Serestina, Tapamo Jules-Raymond
School of Mathematics, Statistics & Computer Science, University of KwaZulu-Natal, Durban 4000, South Africa.
School of Engineering, University of KwaZulu-Natal, Durban 4000, South Africa.
Comput Math Methods Med. 2015;2015:895267. doi: 10.1155/2015/895267. Epub 2015 Feb 22.
Due to noise from uneven contrast and illumination during acquisition process of retinal fundus images, the use of efficient preprocessing techniques is highly desirable to produce good retinal vessel segmentation results. This paper develops and compares the performance of different vessel segmentation techniques based on global thresholding using phase congruency and contrast limited adaptive histogram equalization (CLAHE) for the preprocessing of the retinal images. The results obtained show that the combination of preprocessing technique, global thresholding, and postprocessing techniques must be carefully chosen to achieve a good segmentation performance.
由于在视网膜眼底图像采集过程中存在对比度不均匀和光照等噪声，因此非常需要使用高效的预处理技术来获得良好的视网膜血管分割结果。本文开发并比较了基于全局阈值处理的不同血管分割技术的性能，这些技术使用相位一致性和对比度受限自适应直方图均衡化（CLAHE）对视网膜图像进行预处理。获得的结果表明，必须仔细选择预处理技术、全局阈值处理和后处理技术的组合，以实现良好的分割性能。
