Po-Whei Huang

TL;DR: This method is efficient as it only uses simple operations such as parity check and comparison between average intensities and effective because the detection is based on a hierarchical structure so that the accuracy of tamper localization can be ensured.

TL;DR: A computer-aided system to automatically grade pathological images according to Gleason grading system which is the most widespread method for histological grading of prostate tissues is presented and two feature extraction methods based on fractal dimension are proposed to analyze variations of intensity and texture complexity in regions of interest.

TL;DR: An efficient image retrieval system with high performance of accuracy based on two novel features, the composite sub-band gradient vector and the energy distribution pattern string, which are generated from the sub-images of a wavelet decomposition of the original image.

TL;DR: This paper proposes an automatic system for grading HCC biopsy images using a dual morphological grayscale reconstruction method and proposes a SVM-based decision-graph classifier to classify HCCBiopsy images.

TL;DR: An image enhancement method that combines homomorphic filtering, homogeneity-based contrast stretching, and adaptive morphological transformation is proposed to improve both contrast and illumination evenness of the radiographs simultaneously.