This paper discusses an algorithm incorporating a knowledge-based vision system into an industrial robot system for handling parts intelligently. A continuous fuzzy controller was employed to extract boundary information in a computationally efficient way. The developed algorithm for on-line part recognition using fuzzy logic is shown to be an effective solution to extract the geometric feature...

Given an implication function I defined on the finite chain L = {0, ..., n}, a method for extending I to the set of discrete fuzzy numbers whose support is a set of consecutive natural numbers contained in L (denoted by A1 ) is given. The resulting extension is in fact a fuzzy implication on A1 preserving some boundary properties. Moreover, if the initial implication I is an S, QL or D-implicat...

Edge detection is a primary operation of most of the image processing applications such as image detection, boundary detection, image classification, image registration. Edge detection filters out less important information and preserve the structural properties of image.The Proposed technique uses ANFIS edge detector for edge detection on digital images. It involves a neuro fuzzy system with t...

A multi-direction fuzzy morphology algorithm, for image edge detection is proposed to deal with edge blur and inaccuracy of boundary localization. In the algorithm, two thresholds are selected to conduct image segmentation and image obtaining respectively, fuzzy enhancement for the image is adopted to resolve the loss of edge information and multi-directional structural elements are used to det...

Class imbalance is a prevalent problem that not only reduces the performance of machine learning techniques but also causes lacking inherent complex characteristics data. Though researchers have proposed various ways to deal with problem, they yet consider how select proper treatment, especially when uncertainty levels are high. Applying rough-fuzzy theory imbalanced data could be promising res...

In this paper, we present a rule-based fuzzy segmentation system that is capable of segmenting magnetic resonance (MR) images of diseased human brains into physiologically and pathologically meaningful regions for display and measurement. We have developed a novel technique to automatically generate the membership functions for the fuzzy sets in the antecedent of the IF-THEN fuzzy rules in our ...

Traditional spatial data are generally high dimensional features, and in the clustering of high dimensional data can be directly applied to data processing because of Dimension effect and the data sparseness problem. For CLIQUE algorithm, which usually have the problem such as prone to non-axis direction of overclustering, boundary judgment of fuzzy clustering and smoothing clustering. In this ...

Edge linking is an important task in a boundary extraction problem. In this paper, a fuzzy approach is proposed. The proposed system consists of a fuzzy edge detection module and a fuzzy edge linking module, respectively. The fuzzy edge detector gives a fuzzy membership matrix and an initial edge map. Once the initial edge map is obtained, the pairing of the start and end points of the edges as...

A robust method, fuzzy kNNModel, for toxicity prediction of chemical compounds is proposed. The method is based on a supervised clustering method, called kNNModel, which employs fuzzy partitioning instead of crisp partitioning to group clusters. The merits of fuzzy kNNModel are two-fold: (1) it overcomes the problems of choosing the parameter ε allowed error rate in a cluster, and the parameter...