The researchers studied different types of kernel functions used in a new technique called kernel principal component analysis, which helps extract features from images. They introduced a new combination kernel function that combines local and global features of images, improving the performance of the analysis. By testing it on handwriting and face images, they found that the new kernel function enhances the extraction of features compared to other kernels.