Browsing by Author "Lo, RC"

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Colour image detection and matching using modified generalised Hough transform
(1996-08-01)
Lo, RC
;
Tsai, WH
;
資訊工程學系
;
Department of Computer Science
A new approach to 2-dimensional (2D) colour-image detection and matching using a modified version of the generalised Hough transform (GHT) is proposed. In the conventional GHT. the useful colour information existing in the input image and the relationship between each pixel and its neighbourhood are not used. Furthermore, lighting changes in the image are not usually considered. Therefore, the conventional GHT is seldom applied to colour images. In the proposed approach, lighting changes are removed using normalised colour values, Next, certain critical pixels of an input colour image whose neighbourhoods have larger variances of normalised colour values are extracted. For each critical pixel, a feature vector, which includes the normalised colour values of the pixel as well as those of the pixel's neighbours, is then constructed. A modified voting rule for the GHT is therefore proposed which is based on a similarity-measure function of the feature vectors. High maximum peaks in the cell array are searched finally as the result. The proposed method is robust for colour-image detection and matching in noisy, occlusive, and lighting-change environments, as demonstrated by experimental results.
Colour image detection and matching using modified generalised Hough transform
(1996-08-01)
Lo, RC
;
Tsai, WH
;
資訊工程學系
;
Department of Computer Science
A new approach to 2-dimensional (2D) colour-image detection and matching using a modified version of the generalised Hough transform (GHT) is proposed. In the conventional GHT. the useful colour information existing in the input image and the relationship between each pixel and its neighbourhood are not used. Furthermore, lighting changes in the image are not usually considered. Therefore, the conventional GHT is seldom applied to colour images. In the proposed approach, lighting changes are removed using normalised colour values, Next, certain critical pixels of an input colour image whose neighbourhoods have larger variances of normalised colour values are extracted. For each critical pixel, a feature vector, which includes the normalised colour values of the pixel as well as those of the pixel's neighbours, is then constructed. A modified voting rule for the GHT is therefore proposed which is based on a similarity-measure function of the feature vectors. High maximum peaks in the cell array are searched finally as the result. The proposed method is robust for colour-image detection and matching in noisy, occlusive, and lighting-change environments, as demonstrated by experimental results.
Perspective-transformation-invariant generalized Hough transform for perspective planar shape
(1997-03-01)
Lo, RC
;
Tsai, WH
;
資訊工程學系
;
Department of Computer Science
In the real world, most object shapes are perspectively transformed when imaged. How to recognize or locate such shapes in images is interesting and important. The conventional generalized Hough transform (GHT) is useful for detecting or locating translated two-dimensional (2D) planar shapes. However, it cannot be used for detecting perspectively transformed planar shapes. A new version of the GHT, called perspective-transformation-invariant generalized Hough transform (PTIGHT), is proposed to remove this weakness. The PTIGHT is based on the use of a new perspective reference table that is built up by applying both forward and inverse perspective transformations on a given template shape image from all viewing directions and positions. Due to the use of the point spread function to express the perspective reference table, the required dimensionality of the Hough counting space (HCS) for the PTIGHT is reduced to 2D. After performing the PTIGHT on an input image, the peaks in the HCS whose values are larger than a threshold is picked out as the candidate locations of the perspective shape to be detected in the input images. By performing an inverse PTIGHT on the candidates, one of the candidate locations whose corresponding shape marches best with the input shape is selected and the desired parameters of the perspective transformation can be obtained. Some experimental results are included to demonstrate the applicability of the proposed PTIGHT. (C) 1997 Pattern Recognition Society.
Perspective-transformation-invariant generalized Hough transform for perspective planar shape
(1997-03-01)
Lo, RC
;
Tsai, WH
;
資訊工程學系
;
Department of Computer Science
In the real world, most object shapes are perspectively transformed when imaged. How to recognize or locate such shapes in images is interesting and important. The conventional generalized Hough transform (GHT) is useful for detecting or locating translated two-dimensional (2D) planar shapes. However, it cannot be used for detecting perspectively transformed planar shapes. A new version of the GHT, called perspective-transformation-invariant generalized Hough transform (PTIGHT), is proposed to remove this weakness. The PTIGHT is based on the use of a new perspective reference table that is built up by applying both forward and inverse perspective transformations on a given template shape image from all viewing directions and positions. Due to the use of the point spread function to express the perspective reference table, the required dimensionality of the Hough counting space (HCS) for the PTIGHT is reduced to 2D. After performing the PTIGHT on an input image, the peaks in the HCS whose values are larger than a threshold is picked out as the candidate locations of the perspective shape to be detected in the input images. By performing an inverse PTIGHT on the candidates, one of the candidate locations whose corresponding shape marches best with the input shape is selected and the desired parameters of the perspective transformation can be obtained. Some experimental results are included to demonstrate the applicability of the proposed PTIGHT. (C) 1997 Pattern Recognition Society.