Corner validation based on extracted corner properties

Date

2008-12-01

Author

Bastanlar, Yalin
Yardimci, Yasemin

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

82
views

0
downloads

We developed a method to validate and filter a large set Of previously obtained corner points. We derived the necessary relationships between image derivatives and estimates of corner angle, orientation and contrast. Commonly Used cornerness measures of the auto-correlation matrix estimates of image derivatives are expressed in terms of these estimated corner properties. A candidate corner is validated if the cornerness score directly obtained from the image is sufficiently close to the cornerness score for ail ideal corner with the estimated orientation, angle and contrast. We tested this algorithm oil both real and synthetic images and observed that this procedure significantly improves the corner detection rates based oil human evaluations. We tested the accuracy Of our corner property estimates under various noise conditions. Extracted corner properties call also be used for tasks like feature point matching, object recognition and pose estimation. (c) 2008 Elsevier Inc. All rights reserved.

Subject Keywords

Signal Processing, Software, Computer Vision and Pattern Recognition

URI

https://hdl.handle.net/11511/64499

Journal

COMPUTER VISION AND IMAGE UNDERSTANDING

DOI

https://doi.org/10.1016/j.cviu.2008.05.002

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

Deconvolution and preequalization with best delay LS inverse filters Tuncer, Temel Engin (Elsevier BV, 2004-11-01) A new method for finding the best delay for the design of least-squares (1,S) inverse filters is introduced. It is shown that there is a considerable difference between the LS errors of a best delay filter and an arbitrary LS inverse filter. Proposed method is an effective and computationally efficient approach for the design of LS optimum filters. Deconvolution problem is considered and the MSE performances of pseudoinverse, preequalization and LS inverse filtering are investigated. In this respect, the th...
Object-based image labeling through learning by example and multi-level segmentation Xu, Y; Duygulu, P; Saber, E; Tekalp, AM; Yarman Vural, Fatoş Tunay (Elsevier BV, 2003-06-01) We propose a method for automatic extraction and labeling of semantically meaningful image objects using "learning by example" and threshold-free multi-level image segmentation. The proposed method scans through images, each of which is pre-segmented into a hierarchical uniformity tree, to seek and label objects that are similar to an example object presented by the user. By representing images with stacks of multi-level segmentation maps, objects can be extracted in the segmentation map level with adequate...
One-dimensional representation of two-dimensional information for HMM based handwriting recognition Arica, N; Yarman Vural, Fatoş Tunay (Elsevier BV, 2000-06-01) In this study, we introduce a one-dimensional feature set, which embeds two-dimensional information into an observation sequence of one-dimensional string, selected from a code-book. It provides a consistent normalization among distinct classes of shapes, which is very convenient for Hidden Markov Model (HMM) based shape recognition schemes. The normalization parameters, which maximize the recognition rate, are dynamically estimated in the training stage of HMM. The proposed recognition system is tested on ...
Low-level multiscale image segmentation and a benchmark for its evaluation Akbaş, Emre (Elsevier BV, 2020-10-01) In this paper, we present a segmentation algorithm to detect low-level structure present in images. The algorithm is designed to partition a given image into regions, corresponding to image structures, regardless of their shapes, sizes, and levels of interior homogeneity. We model a region as a connected set of pixels that is surrounded by ramp edge discontinuities where the magnitude of these discontinuities is large compared to the variation inside the region. Each region is associated with a scale that d...
Camera auto-calibration using a sequence of 2D images with small rotations Hassanpour, R; Atalay, Mehmet Volkan (Elsevier BV, 2004-07-02) In this study, we describe an auto-calibration algorithm with fixed but unknown camera parameters. We have modified Triggs' algorithm to incorporate known aspect ratio and skew values to make it applicable for small rotation around a single axis. The algorithm despite being a quadratic one is easy to solve. We have applied the algorithm to some artificial objects with known size and dimensions for evaluation purposes. In addition, the accuracy of the algorithm has been verified using synthetic data. The des...

Citation Formats

Y. Bastanlar and Y. Yardimci, “Corner validation based on extracted corner properties,” COMPUTER VISION AND IMAGE UNDERSTANDING, pp. 243–261, 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/64499.