Yung-hui Li

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Current state-of-the-art approach for performing face sketch recognition transforms all the test face images into sketches, and then performs recognition on sketch domain using the sketch composite. In our approach we propose the opposite; which has advantages in a real-time sysrtem; we propose to generate a realistic face image from the composite sketch(More)
—Traditionally, iris recognition is always about analyzing and extracting features from iris texture. We proposed to investigate regions around eyelashes and extract useful information which helps us to perform ethnic classification. We propose an algorithm which is easy to implement and effective. First, we locate eyelash region by using ASM to model(More)
On normalized iris images, there are many kinds of noises, such as eyelids, eyelashes, shadows or specular reflections, that often occlude the true iris texture. If high recognition rate is desired, those occluded areas must be estimated accurately in order for them to be excluded during the matching stage. In this paper, we propose a unified, probabilistic(More)
Iris masks play an important role in iris recognition. They indicate which part of the iris texture map is useful and which part is occluded or contaminated by noisy image artifacts such as eyelashes, eyelids, eyeglasses frames, and specular reflections. The accuracy of the iris mask is extremely important. The performance of the iris recognition system(More)
Most face recognition systems focus on photo-based (or video) face recognition, but there are many law-enforcement applications where a police sketch artist composes a face sketch of the criminal and that is used by the officers to look for the criminal. Currently state-of-the-art research approach transforms all test face images into sketches then perform(More)