14,353 research outputs found
Using shape entropy as a feature to lesion boundary segmentation with level sets
Accurate lesion segmentation in retinal imagery is an area of vast research. Of the many segmentation methods
available very few are insensitive to topological changes on noisy surfaces. This paper presents an extension to
earlier work on a novel stopping mechanism for level sets. The elementary features scheme (ELS) in [5] is
extended to include shape entropy as a feature used to ’look back in time’ and find the point at which the curve
best fits the real object. We compare the proposed extension against the original algorithm for timing and
accuracy using 50 randomly selected images of exudates with a database of clinician demarcated boundaries as
ground truth. While this work is presented applied to medical imagery, it can be used for any application
involving the segmentation of bright or dark blobs on noisy images
A robust lesion boundary segmentation algorithm using level set methods
This paper addresses the issue of accurate lesion segmentation in retinal imagery, using level set methods and
a novel stopping mechanism - an elementary features scheme. Specifically, the curve propagation is guided
by a gradient map built using a combination of histogram equalization and robust statistics. The stopping
mechanism uses elementary features gathered as the curve deforms over time, and then using a lesionness
measure, defined herein, ’looks back in time’ to find the point at which the curve best fits the real object.
We compare the proposed method against five other
segmentation algorithms performed on 50 randomly selected images of exudates with a database of clinician
demarcated boundaries as ground truth
Lesion boundary segmentation using level set methods
This paper addresses the issue of accurate lesion segmentation in retinal imagery, using level set methods and
a novel stopping mechanism - an elementary features scheme. Specifically, the curve propagation is guided by a gradient map built using a combination of histogram equalization and robust statistics. The stopping mechanism uses elementary features gathered as the curve deforms over time, and then using a lesionness measure, defined herein, ’looks back in time’ to find the point at which the curve best fits the real object. We implement the level set using a fast upwind scheme and compare the proposed method against five other
segmentation algorithms performed on 50 randomly selected images of exudates with a database of clinician
marked-up boundaries as ground truth
Fuzzy geometry, entropy, and image information
Presented here are various uncertainty measures arising from grayness ambiguity and spatial ambiguity in an image, and their possible applications as image information measures. Definitions are given of an image in the light of fuzzy set theory, and of information measures and tools relevant for processing/analysis e.g., fuzzy geometrical properties, correlation, bound functions and entropy measures. Also given is a formulation of algorithms along with management of uncertainties for segmentation and object extraction, and edge detection. The output obtained here is both fuzzy and nonfuzzy. Ambiguity in evaluation and assessment of membership function are also described
A fuzzy measure approach to motion frame analysis for scene detection
This paper addresses a solution to the problem of scene estimation of motion video data in the fuzzy set theoretic framework. Using fuzzy image feature extractors, a new algorithm is developed to compute the change of information in each of two successive frames to classify scenes. This classification process of raw input visual data can be used to establish structure for correlation. The algorithm attempts to fulfill the need for nonlinear, frame-accurate access to video data for applications such as video editing and visual document archival/retrieval systems in multimedia environments
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Industrial application of fuzzy systems; adaptive fuzzy control of solder paste stencil printing
This paper presents an adaptive fuzzy control algorithm for the control of the solder paste stencil printing stage of surface mount printed circuit board assembly. The proposed method of automatic solder paste stencil printing consist of four blocks; fuzzy feature extraction, defect classifcation of paste deposits, adaptive fuzzy rule-based model identifcation and subsequently an optimal control action for the stencil printing process. Experimental results are presented to illustrate the capability of the algorithm
A review of wildland fire spread modelling, 1990-present 3: Mathematical analogues and simulation models
In recent years, advances in computational power and spatial data analysis
(GIS, remote sensing, etc) have led to an increase in attempts to model the
spread and behvaiour of wildland fires across the landscape. This series of
review papers endeavours to critically and comprehensively review all types of
surface fire spread models developed since 1990. This paper reviews models of a
simulation or mathematical analogue nature. Most simulation models are
implementations of existing empirical or quasi-empirical models and their
primary function is to convert these generally one dimensional models to two
dimensions and then propagate a fire perimeter across a modelled landscape.
Mathematical analogue models are those that are based on some mathematical
conceit (rather than a physical representation of fire spread) that
coincidentally simulates the spread of fire. Other papers in the series review
models of an physical or quasi-physical nature and empirical or quasi-empirical
nature. Many models are extensions or refinements of models developed before
1990. Where this is the case, these models are also discussed but much less
comprehensively.Comment: 20 pages + 9 pages references + 1 page figures. Submitted to the
International Journal of Wildland Fir
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