• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.3
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• pp.237-246
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• 2001

A high speed context-free marker-controlled and minima imposition-free watershed transform is proposed for efficient multi-object detection and segmentation from a complex background. The context-free markers are extracted from a complex backgrounded multi-object image using a noise tolerant attention operator. These make marker-controlled watershed possible for the over-segmentation reduction without region merging. The proposed method presents a marker-constrained labeling that can speed up the segmentation of a marker-controlled watershed transform by eliminating the necessity of the minima imposition. Simulation results show that the proposed method can efficiently detects and segments multiple objects from a complex background while reducing over- segmentation and the computation time.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.482-485
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• 2000

A modified watershed transform is proposed which is context-free marker-controlled and minima imposition-free to reduce the over-segmentation and to speedup the transform. In contrast to the conventional methods in which a priori knowledge, such as flat zones, zones of homogeneous texture, and morphological distance, is required for marker extraction, context-free marker extraction is proposed by using the attention operator based on the GST (generalized symmetry transform). By using the context-free marker, the proposed watershed transform exploit marker-constrained labeling to speedup the computation and to reduce the over-segmentation by eliminating the unnecessary geodesic reconstruction such as the minima imposition and thereby eliminating the necessity of the post-processing of region merging. The simulation results show that the proposed method can extract context-free markers inside the objects from the complex background that includes multiple objects and efficiently reduces over-segmentation and computation time.

• Journal of Korea Multimedia Society
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• v.10 no.4
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• pp.441-449
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• 2007

In clustering for image segmentation, large amount of computation and typical segmentation errors have been important problems. In the paper, we suggest a new method for minimizing these problems. Markers in marker-controlled watershed transform represent segmented areas because they are starting-points of extending areas. Thus, clustering restricted by marker pixels can reduce computational complexity. In our proposed method, the markers are selected by Gabor texture energy, and cluster information of them are generated by FCM (fuzzy c-mean) clustering. Generated areas from watershed transform are merged by using cluster information of markers. In the test of Brodatz' texture images, we improved typical partition-errors obviously and obtained less computational complexity compared with previous FCM clustering algorithms. Overall, it also took regular computational time.

• Journal of Korea Multimedia Society
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• v.17 no.10
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• pp.1171-1181
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• 2014

In this paper, we propose improved methods which are image conversion and extraction method of watershed seed using morphological characteristic of teeth on complement image. Conventional tooth segmentation methods are occurred low detection ratio at molar region and over, overlap segmentation owing to specular reflection and morphological feature of molars. Therefore, in order to solve the problems of the conventional methods, we propose the image conversion method and improved extraction method of watershed seed. First, the image conversion method is performed using RGB, HSI space of tooth image for to extract boundary and seed of watershed efficiently. Second, watershed seed is reconstructed using morphological characteristic of teeth. Last, individual tooth segmentation is performed using proposed seed of watershed by watershed algorithm. Therefore, as a result of comparison with marker controlled watershed algorithm and the proposed method, we confirmed higher detection ratio and accuracy than marker controlled watershed algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.3
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• pp.1-1
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• 2001

본 논문에서는 복잡 배경으로부터 임의의 다중물체를 효과적으로 검출함과 동시에 고속 분할할 수 있는 문맥자유 마커제어 분수계 변환 (context-free marker controlled watershed transform)을 제안하였다. 먼저 잡음에 강건한 주목 연산자 (attention operator)를 써서 복잡 배경 속의 여러 물체 별로 그 위치를 검출하여 문맥자유 마커를 추출하고, 이를 마커로 한정된 레이블링 (marker constrained labeling)을 하여 최소값 부과과정이 필요 없는 문맥자유 마커제어 분수계 변환을 제안함으로써 과분할없이 신속하게 분할할 수 있도록 하였다. 다중 물체가 포함된 복잡 영상에 적용 실험하여, 대상 물체에 대한 사전정보 없이도 과분할과 처리시간을 대폭 줄여 효과적으로 다중 물체를 검출함과 동시에 고속 분할이 가능함을 확인 할 수 있었다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.1
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• pp.210-216
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• 2010

In this study, we propose a novel method to segment an individual tooth region in a true color image. The difference of the intensity in RGB is initially extracted and subsequent morphological reconstruction is applied to minimize the spurious segmentation regions. Multiple seeds in the tooth regions are chosen by searching regional minima and a Sobel-mask edge operations is performed to apply MCWA(Marker-Controlled Watershed Algorithm). As the results of applying MCWA transform for our proposed tooth segmentation algorithm, the individual tooth region can be resolved in a CCD tooth color image.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1136-1142
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• 2010

In this study, an efficient removal algorithm for specular reflections in a tooth color image is proposed to minimize the artefact interrupting color image segmentation. The pixel values of RGB color channels are initially reversed to emphasize the features in reflective regions, and then those regions are automatically detected by utilizing perceptron artificial neural network model and those prominent intensities are corrected by applying a smoothing spatial filter. After correcting specular reflection regions, multiple seeds in the tooth candidates are selected to find the regional minima and MCWA(Marker-Controlled Watershed Algorithm) is applied to delineate the individual tooth region in a CCD tooth color image. Therefore, the accuracy in segmentation for separating tooth regions can be drastically improved with removing specular reflections due to the illumination effect.