A survey of thresholding techniques
Computer Vision, Graphics, and Image Processing
Performance study of several global thresholding techniques for segmentation
Computer Vision, Graphics, and Image Processing
An analysis of histogram-based thresholding algorithms
CVGIP: Graphical Models and Image Processing
A survey of automated visual inspection
Computer Vision and Image Understanding
Image histogram thresholding based on multiobjective optimization
Signal Processing
Optimal multi-level thresholding using a two-stage Otsu optimization approach
Pattern Recognition Letters
A pattern recognition and adaptive approach to quality control
WSEAS Transactions on Systems and Control
Fractional differentiation and non-Pareto multiobjective optimization for image thresholding
Engineering Applications of Artificial Intelligence
Image acquisition and automated inspection of wine bottlenecks by tracking in multiple views
ISCGAV'08 Proceedings of the 8th conference on Signal processing, computational geometry and artificial vision
A thresholding method based on two-dimensional fractional differentiation
Image and Vision Computing
Detecting mitochondria in fluorescence images
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Optimal threshold selection for tomogram segmentation by reprojection of the reconstructed image
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
EA'07 Proceedings of the Evolution artificielle, 8th international conference on Artificial evolution
Continuous force field analysis for generalized gradient vector flow field
Pattern Recognition
An automatic thresholding for crack segmentation based on convex residual
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part I
Unsupervised range-constrained thresholding
Pattern Recognition Letters
An adaptable threshold detector
Information Sciences: an International Journal
Small object detection in cluttered image using a correlation based active contour model
Pattern Recognition Letters
A modified valley-emphasis method for automatic thresholding
Pattern Recognition Letters
Image bilevel thresholding based on multiscale gradient multiplication
Computers and Electrical Engineering
Image bilevel thresholding based on stable transition region set
Digital Signal Processing
Artificial Intelligence in Medicine
A hybrid plaque characterization method using intravascular ultrasound images
Technology and Health Care
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Automatic thresholding has been widely used in the machine vision industry for automated visual inspection of defects. A commonly used thresholding technique, the Otsu method, provides satisfactory results for thresholding an image with a histogram of bimodal distribution. This method, however, fails if the histogram is unimodal or close to unimodal. For defect detection applications, defects can range from no defect to small or large defects, which means that the gray-level distributions range from unimodal to bimodal. For this paper, we revised the Otsu method for selecting optimal threshold values for both unimodal and bimodal distributions, and tested the performance of the revised method, the valley-emphasis method, on common defect detection applications.