• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.34S no.3
• /
• pp.97-107
• /
• 1997

Image segmentation is teh important step in image infromation extraction for computer vison sytems. Fuzzy clustering methods have been used extensively in color image segmentation. Most analytic fuzzy clustering approaches are derived from the fuzzy c-means (FCM) algorithm. The FCM algorithm uses th eprobabilistic constraint that the memberships of a data point across classes sum to 1. However, the memberships resulting from the FCM do not always correspond to the intuitive concept of degree of belongingor compatibility. moreover, the FCM algorithm has considerable trouble above under noisy environments in the feature space. Recently, the possibilistic C-mean (PCM) for solving growing for color image segmentation. In the PCM, the membersip values may be interpreted as degrees of possibility of the data points belonging to the classes. So, the problems in the FCM can be solved by the PCM. The clustering results by just PCM are not smoothly bounded, and they often have holes. So, the region growing was used as a postprocessing. In our experiments, we illustrated that the proposed method is reasonable than the FCM in noisy enviironments.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.5
• /
• pp.519-524
• /
• 2006

Segmentation for the region of nucleus in the image of uterine cervical cytodiagnosis is known as the most difficult and important part in the automatic cervical cancer recognition system. In this paper, the region of nucleus is extracted from an image of uterine cervical cytodiagnosis using the fuzzy grey morphology operation. The characteristics of the nucleus are extracted from the analysis of morphemetric features, densitometric features, colormetric features, and textural features based on the detected region of nucleus area. The classification criterion of a nucleus is defined according to the standard categories of the Bethesda system. The enhanced fuzzy ART algorithm is used to the extracted nucleus and the results show that the proposed method is efficient in nucleus recognition and uterine cervical Pap-Smears extraction.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2000.04a
• /
• pp.253-257
• /
• 2000

the objective of this study is to design and evaluate a methodology for diagnosing the appendicitis in a fuzzy neural network that integrates the partition of input space by fuzzy entropy and the generation of fuzzy control rules and learning algorithm. In particular the diagnosis of appendicitis depends on the rule of thumb of the experts such that it associates with the region, the characteristics, the degree of the ache and the potential symptoms. In this scheme the basic idea is to realize the fuzzy rle base and the process of reasoning by neural network and to make the corresponding parameters of the fuzzy control rules be adapted by back propagation learning rule. To eliminate the number of the parameters of the rules, the output of the consequences of the control rules is expressed by the network's connection weights. As a result we obtain a method for reducing the system's complexities. Through computer simulations the effectiveness of the proposed strategy is verified for the diagnosis of appendicitis.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1949-1954
• /
• 2005

One of control methods for underactuated manipulators is known as a switching control which selects a partially-stable controller using a prespecified switching rule. A switching computed torque control with a fuzzy energy region method was proposed. In this approach, some partly stable controllers are designed by the computed torque method, and a switching rule is based on fuzzy energy regions. Design parameters related to boundary curves of fuzzy energy regions are optimized offline by a genetic algorithm (GA). In this paper, we discuss on parameters obtained by GA. The effectiveness of the switching fuzzy energy method is demonstrated with some simulations.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.4 no.2
• /
• pp.142-148
• /
• 2004

In this paper, we propose the color fuzzy decision algorithm to face segmentation in a color image. Our algorithm can segment without the user's interaction by fuzzy decision marking. And it removes small parts such as a noise using wavelet morphology in the image obtained by applying the fuzzy decision algorithm. Also, it merges and chooses the face region in each quantization image through rough sets. This video object division algorithm is shown to be superior to a conventional algorithm.

• Proceedings of the KIEE Conference
• /
• 2001.11c
• /
• pp.169-171
• /
• 2001

Unlike rigid objects, the edge intensity of a gaseous object is various along the object boundary (edge intensities of some pixels on a gaseous object boundary are weaker than those of small rigid objects or noise itself). Therefore, the conventional edge detectors may not adequately detect boundary-like edge pixels for gaseous objects. In this paper A new methodology for segmenting gaseous object images is introduced. Proposed method consists of fuzzy-based boundary detector applicable to gaseous as well as rigid objects and concave region filling to recover object regions.

• Proceedings of the IEEK Conference
• /
• 1999.06a
• /
• pp.777-780
• /
• 1999

In this paper, a fuzzy logic controller is designed for speed control of a hydraulic inverter elevator. Mathematical modeling of an elevator actuated with hydraulic system is presented and the friction characteristics of a cylinder is examined, which may cause the abrupt increase of the acceleration in the zero-crossing speed region. Simulation results show that the proposed fuzzy logic speed controller yields a better control performance than conventional PID controller.

• Proceedings of the KIEE Conference
• /
• 2001.11c
• /
• pp.22-25
• /
• 2001

In this paper, a fuzzy advance angle control method is described to drive an industrial low voltage SRM (Switched Reluctance Motor) for 10kW forklift truck. SRM has a highly non-linear characteristic that is due to change the rotor and stator. And low voltage SRM is designed that its phase resistance and phase inductance is very low to inject high current into the phase windings. In this reason, the proper current control is necessary to drive the low voltage SRM efficiently. SRM has positive torque at increasing inductance region and negative torque at decreasing inductance region. Due to this reason, the current has to be built up in the increasing phase inductance part as soon as possible. Therefore, the phase switch must be turned on before the phase inductance increases, and this angle is called as the advance angle. Also, the phase current has to be dropped before the phase inductance decreases. Fuzzy logic is a flexible and general-purposed method of implementing non-linear functions and as such it is useful in control applications. Consequently, we designed a fuzzy advance angle controller to control the phase current appropriately.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2005.05b
• /
• pp.237-240
• /
• 2005

As a part of the effort for improving the durability design based on a set of the deem-to-satisfy specifications, it is important and primary to quantitatively identify the environmental impact to a target reinforced concrete structure. In this work, an effort is made to quantitatively calculate the environmental affecting factor with using a fuzzy inference that it indicates the severity of environmental impact to the exposed reinforced concrete structure or member. This system is composed of input region, output region and rule base. For developing the fuzzy inference system surface chloride concentration{chloride), cyclic degree of wet and dry(CWD), relative humidity(RH) and temperature (TEMP) were selected as the input parameter to environmental affecting factor(EAF) of output parameter. The Rules in inference engine are generated from the engineering knowledge and intuition based on some international code of practises as well as various researcher's experimental data. The devised fuzzy inference system was verified comparing the inferred value with the investigation data, and proved to be validated. Thus it is anticipated that this system for quantifying EAF is certain to be considered into the starting point to develop the performance-based durability design considering the service life of structure.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.8
• /
• pp.1477-1481
• /
• 2010

In this paper, we propose the classification and tracking method of the hand region using deformable template and condensation. To do this, first, we extract the hand region by using the fuzzy color filter and HCbCr color model. Second, we extract the edge of hand by applying the Canny edge algorithm. Third, we find the first template by calculating the conditional probability between the extracted edge and the model edge. If the accurate template of the first object is decided, the condensation algorithm tries to track it. Finally, we demonstrate the effectiveness and feasibility of the proposed method through some experiments.