Browsing by Author "Hsueh, YC"

Now showing 1 - 13 of 13

A modified morphological corner detector
(1998-03-01)
Lin, RS
;
Chu, CH
;
Hsueh, YC
;
資訊工程學系
;
Department of Computer Science
In this paper we propose a modified morphological corner detection method which finds convex and concave significant points using simple integer computation. We use the morphological peak extractor to detect convex corners and use a modified valley extractor to detect concave corners. Moreover, information of the distances between pixels on the boundary segment determined by two contiguous significant points and the chord connecting these two contiguous significant points can be applied to remedy the loosing corner due to the shape of the chosen structuring element. (C) 1998 Elsevier Science B.V. All rights reserved.
A new method for texture analysis using morphological gradient texture histograms
(1996-05-01)
Lee, JH
;
Hsueh, YC
;
交大名義發表
;
資訊工程學系
;
National Chiao Tung University
A new method using Morphological Gradients, which measures the degree of roughness of image surface, is proposed for texture analysis. In this method, the local texture feature for a given pixel is characterized by its corresponding morphological gradient, and the global texture aspect of an image, denoted the Morphological Gradient Texture Histogram (MGTH), is used as a distinguishing feature for texture analysis and classification. To evaluate the performance of the proposed method, supervised texture classification and rotated texture classification are applied. Experimental results reveal high accuracy classification rates and show that the proposed method is a good tool for texture analysis.
A new method for texture analysis using morphological gradient texture histograms
(1996-05-01)
Lee, JH
;
Hsueh, YC
;
資訊工程學系
;
Department of Computer Science
A new method using Morphological Gradients, which measures the degree of roughness of image surface, is proposed for texture analysis. In this method, the local texture feature for a given pixel is characterized by its corresponding morphological gradient, and the global texture aspect of an image, denoted the Morphological Gradient Texture Histogram (MGTH), is used as a distinguishing feature for texture analysis and classification. To evaluate the performance of the proposed method, supervised texture classification and rotated texture classification are applied. Experimental results reveal high accuracy classification rates and show that the proposed method is a good tool for texture analysis.
Comparative study on morphological skeletonization and fuzzy medial axis transformation
(2002-01-01)
Jan, SR
;
Hsueh, YC
;
資訊工程學系
;
Department of Computer Science
In this paper, we make a comparative study on morphological skeletonization (MSK) and fuzzy medial axis transformation (FMAT), Methods have been proposed to construct convex FMAT from the morphological skeleton points and to translate FMAT to MSK respectively. For the case of translating MSK to convex FMAT the experimental results reveal that the combination of the proposed method and the redundant removal algorithm is very effective. Especially, the combined method is faster than the original method for constructing convex FMAT of smoothed images. (C) 2002 SPIE and IST.
Detail-preserving smoothing with morphology and fuzzy reasoning
(1996-07-01)
Lee, YG
;
Hsueh, YC
;
交大名義發表
;
資訊工程學系
;
National Chiao Tung University
This study investigates a new approach to removing noise that preserves the fine details which are based on combination of mathematical morphology and fuzzy reasoning. We extract some features from an image using mathematical morphology, then input these features, and the image itself into fuzzy-rule-based systems to produce a more graceful image. (C) 1996 SPIE and IS&T.
Fuzzy logic approach for removing noise
(1995-12-01)
Lee, YG
;
Hsueh, YC
;
交大名義發表
;
資訊工程學系
;
National Chiao Tung University
This paper shows how fuzzy reasoning techniques can be applied on smoothing filters design. It uses the fuzzy concept to decide whether a pixel in an image is a noise one or not in order to achieve maximum noise reduction in uniform areas and preserve details as well.
Multichannel filtering by gradient information
(2000-02-01)
Lin, RS
;
Hsueh, YC
;
資訊工程學系
;
Department of Computer Science
In this paper, multichannel image filtering using local gradient information is studied and evaluated which is simpler and more appropriate than the traditional approaches that have been addressed by means of groupwise vector ordering information. Two adaptive weighted multichannel filters based on local gradient information to noise removal in color images are introduced. The first proposed multichannel filter is rather highly effective for Gaussian and Uniform noise removal in preserving good edges. The second proposed multichannel filter is robust to Gaussian, Uniform, Impulse noise, and Gaussian noise mixed with outliers. (C) 2000 Elsevier Science B.V. All rights reserved.
Primitive spatial relations based on SKIZ
(2000-05-15)
Jan, SR
;
Hsueh, YC
;
資訊工程學系
;
Department of Computer Science
Spatial relations between objects or regions in an image play important roles in scene understanding. However, it is difficult to define these relations for automation. Most existing methods for defining spatial relations depend on angle measurements between points of the two objects of interest. In this study, we propose a new approach based on the concept of skeleton by zones of influence (SKIZ) for recognizing the primitive spatial relations between objects or regions in a segmented image. The approach is compared with the aggregation and compatibility methods. The experimental result shows the proposed approach is effective and fast. (C) 2000 Elsevier Science B.V. All rights reserved.
Relation-based variations of the discrete radon transform
(1996-02-01)
Hsueh, YC
;
交大名義發表
;
資訊工程學系
;
National Chiao Tung University
;
Department of Computer Science
The finite Radon transform was introduced by Bolker around 1976. Since then, many variations of the discrete Radon transform have been proposed. In this paper, we first propose a variation of the discrete Radon transform which is based on a binary relation. Then, we generalize this variation to weighted Radon transformation based on a weighted relation. Under such generalization, we show that discrete convolution is a special case of weighted Radon transformation. To further generalize Radon transformation to be defined on lattice-valued functions, we propose two nonlinear variations of Radon transformation. These two nonlinear variations have very close relations with morphological operations. Finally, we generalize Matheron's representation theorem to represent translation-invariant operations on functions from an abelian group to a complete lattice.
Some modifications of gradient weighted filters
(1999-12-01)
Lin, RS
;
Hsueh, YC
;
資訊工程學系
;
Department of Computer Science
Gradient weighted filters are locally adaptive weighted mean filters. In this paper, a general formulation of gradient weighted filters with some characteristic parameters was derived first from existing gradient weighted filters. Then we propose some modifications by varying these parameters. We modify gradient inverse weighted filters, characterize filters into first and second order filters, and propose Pi filters. Moreover, an imposed criterion for second order filters to preserve fine details was introduced to promote the existing gradient weighted filters. Finally, a criterion to combine first and second order filters was proposed to remove noise with mixed types, Throughout this paper, rational analysis and experimental results demonstrate the efficiency of the proposed methods. (C) 1999 Academic Press.
Texture classification using fuzzy uncertainty texture spectrum
(1998-08-01)
Lee, YG
;
Lee, JH
;
Hsueh, YC
;
資訊工程學系
;
Department of Computer Science
A new method using fuzzy uncertainty, which measures the uncertainty of the uniform surface in an image, is proposed for texture analysis. A grey-scale image can be transformed into a fuzzy image by the uncertainty definition. The distribution of the membership in a measured fuzzy image, denoted by the fuzzy uncertainty texture spectrum (FUTS), is used as the texture feature for texture analysis. To evaluate the performance of the proposed method, supervised texture classification and rotated texture classification are applied. Experimental results reveal high-accuracy classification rates and show that the proposed method is a good tool for texture analysis. (C) 1998 Elsevier Science B.V. All rights reserved.
Thresholdings, umbrae, residuals, and surpluses of L-images
(1994)
Hsueh, YC
;
資訊工程學系
;
Department of Computer Science
Window-size determination for granulometrical structural texture classification
(1998-04-01)
Jan, SR
;
Hsueh, YC
;
資訊工程學系
;
Department of Computer Science
In this paper we present a method to predict the window size when determining the local granulometry for a structural texture image set. The proposed method is based on the concept of periodicity property of structural texture images. It suggests that one may choose the minimum odd number not less than the maximum periods of texture images as a window size. (C) 1998 Elsevier Science B.V. All rights reserved.