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Journal ArticleDOI

Fast radial symmetry for detecting points of interest

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TLDR
A new transform is presented that utilizes local radial symmetry to highlight points of interest within a scene and is seen to offer equal or superior performance to contemporary techniques at a relatively low-computational cost.
Abstract
A new transform is presented that utilizes local radial symmetry to highlight points of interest within a scene. Its low-computational complexity and fast runtimes makes this method well-suited for real-time vision applications. The performance of the transform is demonstrated on a wide variety of images and compared with leading techniques from the literature. Both as a facial feature detector and as a generic region of interest detector the new transform is seen to offer equal or superior performance to contemporary techniques at a relatively low-computational cost. A real-time implementation of the transform is presented running at over 60 frames per second on a standard Pentium III PC.

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Citations
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Proceedings ArticleDOI

Robust Face Recognition via Accurate Face Alignment and Sparse Representation

TL;DR: A robust real-time facial recognition system featuring a new cascade framework including two different methods for eye detection and face alignment, and a new approach for face detection termed Boosted Greedy Sparse Linear Discriminant Analysis (BGSLDA).
Journal ArticleDOI

Cell segmentation for immunofluorescence multiplexed images using two-stage domain adaptation and weakly labeled data for pre-training

TL;DR: In this paper , a two-stage domain adaptation was proposed to train a Mask R-CNN model for cell segmentation using nuclear (DAPI) and membrane (Na+K+ATPase) stained images.

Visual Yield Estimation in Vineyards: Experiments with Different Varietals and Calibration Procedures

TL;DR: An approach to predict the vineyard yield automatically and nondestructively with cameras is presented and it is found that it can predict yield of individual vineyard rows to within 10% and overall yield to within 5% of the actual harvest weight.
Proceedings ArticleDOI

Retinal vessel extraction by combining radial symmetry transform and iterated graph cuts

TL;DR: A new radial symmetry transformation, which is based on line kernels, is proposed to improve the detection of vessel structures and restrain the response of nonvessel structures, and an iterated segmentation algorithm is used to extract retinal vessels.
Journal ArticleDOI

Automatic extraction of go game positions from images: a multi-strategical approach to constrained multi-object recognition

TL;DR: A constrained object recognition task that has been robustly solved largely with simple machine learning methods, using a small corpus of about 100 images taken under a variety of lighting conditions, and is complementary to Seewald (2003), which focuses on solving the same task using different sensors.
References
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Journal ArticleDOI

Use of the Hough transformation to detect lines and curves in pictures

TL;DR: It is pointed out that the use of angle-radius rather than slope-intercept parameters simplifies the computation further, and how the method can be used for more general curve fitting.

Image Features From Phase Congruency

Peter Kovesi
TL;DR: Videre: Journal of Computer Vision Research is a quarterly journal published electronically on the Internet by The MIT Press, Cambridge, Massachusetts, 02142 and prices subject to change without notice.
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Finding circles by an array of accumulators

TL;DR: This procedure is an extension and improvement of the circle-finding concept sketched by Duda and Hart as an extension of the Hough straight-line finder.
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Algorithms for defining visual regions-of-interest: comparison with eye fixations

TL;DR: This paper investigates and develops a methodology that serves to automatically identify a subset of aROIs (algorithmically detected ROIs) using different image processing algorithms (IPAs), and appropriate clustering procedures, and compares hROIs with hROI as a criterion for evaluating and selecting bottom-up, context-free algorithms.
Journal ArticleDOI

Context-free attentional operators: the generalized symmetry transform

TL;DR: An attention operator based on the intuitive notion of symmetry, which generalized many of the existing methods of detecting regions of interest is presented, a low-level operator that can be applied successfully without a priori knowledge of the world.