Nelson Yung

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This paper proposes a new method for fabric defect classification by incorporating the design of a wavelet frames based feature extractor with the design of a Euclidean distance based classifier. Channel variances at the outputs of the wavelet frame decomposition are used to characterize each nonoverlapping window of the fabric image. A feature extractor(More)
In this paper, a vehicle shape approximation method based on the vehicle motion in a typical traffic image sequence is proposed. In the proposed method, instead of using the 2D image data directly, the intrinsic 3D data is estimated in a monocular image sequence. Given the binary vehicle mask and the camera parameters, the vehicle shape is estimated by the(More)
This paper describes a fully integrated mobile vehicle simulator EXPECTATIONS. The structure of the simulator is one of modular and object-oriented, where the virtual environment, static and dynamic objects and their interactions are hierarchically constructed. It supports 2D/3D real-time graphic rendering of the composite environment, which can be(More)
The classification of defects is highly demanded for automated inspection of textile products. In this paper, a new method for textile defect classification is proposed by using discriminative wavelet frames. Multiscale texture properties of textile image are characterized by its wavelet frames representation. For a better description of the latent(More)
Corners play an important role in object identification methods used in machine vision and image processing systems. Single-scale feature detection finds it hard to detect both fine and coarse features at the same time. On the other hand, multi-scale feature detection is inherently able to solve this problem. This paper proposes an improved multi-scale(More)
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