RESEARCH HIGHLIGHTS IN IAS

Authors

  • Marko Kreft Biotechnical Faculty, University of Ljubljana

DOI:

https://doi.org/10.5566/ias.1731

Keywords:

image analysis, stereology, computer vision, process modelling

Abstract

We are reviewing and commenting highlights of the research published in Image Analysis and Stereology journal (IAS), volume 35, where 16 original research papers on image analysis, computer vision, modelling, and other approaches were published. We have reported on the precision of curve length estimation in the plane. Further, a focus was on a robust estimation technique for 3D point cloud registration. Next contribution in computer vision was on the accuracy of stereo matching algorithm based on illumination control. An attempt was also made to automatically diagnose prenatal cleft lip with representative key points and identify the type of defect in three-dimensional ultrasonography. Similarly, a new report is presenting estimation of torsion of digital curves in 3D images and next, the nuchal translucency by ultrasound is being analyzed. Also in ophthalmology, image analysis may help physicians to establish a correct diagnosis, which is supported by a new approach to measure tortuosity of retinal vessel. Another report of medical significance analyzed correlation of the shape parameters for characterization of images of corneal endothelium cells. Shape analysis is also an important topic in material science, e.g. in analyzing fine aggregates in concrete. As in concrete, in fiber reinforced composites image analysis may aid in improved quality, where the direction of fibers have decisive impact on properties. Automatic defect detection using a computer vision system improves productivity quality in industrial production, hence we report of a new Haar wavelet-based approach.

References

Blankenburg C, Daul C, Ohser J (2016). Estimating torsion of digital curves using 3d image analysis. Image Anal Stereol 35:81-91.

Gomez A, Cruz M, Cruz-Orive L (2016). On the precision of curve length estimation in the plane. Image Anal Stereol 35:1-14.

Gotovac V, Helisova K, Ugrina I (2016). Assessing dissimilarity of random sets through convex compact approximations, support functions and envelope tests. Image Anal Stereol 35:181-93.

Hamzah R, Ibrahim H, Abu Hassan A (2016). Stereo matching algorithm based on illumination control to improve the accuracy. Image Anal Stereol 35:39-52.

He H, Courard L, Pirard E, Michel F (2016). Shape analysis of fine aggregates used for concrete. Image Anal Stereol 35:159-66.

Kostopoulos S, Glotsos D, Asvestas P, Konstandinou C, Xenogiannopoulos G, Sidiropoulos K, Nikolatou E, Perakis K, Mantzouratos S, Sakkis T, Sakellaropoulos G, Nikiforidis G, Cavouras D (2016). An ensemble template matching and content-based image retrieval scheme towards early stage detection of melanoma. Image Anal Stereol 35:137-48.

Mapayi T, Tapamo J, Viriri S, Adio A (2016). Automatic retinal vessel detection and tortuosity measurement. Image Anal Stereol 35:117-35.

Mohamadzadeh S, Farsi H (2016). Content based video retrieval based on hdwt and sparse representation. Im-age Anal Stereol 35:67-80.

Nurzynska K, Piorkowski A (2016). The correlation analysis of the shape parameters for endothelial image characterisation. Image Anal Stereol 35:149-58.

Oyebode K, Tapamo J (2016). Adaptive parameter selection for graph-cut based segmentation on cell im-ages. Image Anal Stereol 35:29-37.

Pankaj D, Nidamanuri R (2016). A robust estimation technique for 3d point cloud registration. Image Anal Stereol 35:15-28.

Sciortino G, Orlandi E, Valenti C, Tegolo D (2016). Wavelet analysis and neural network classifiers to de-tect mid-sagittal sections for nuchal translucency measurement. Image Anal Stereol 35:105-15.

Sujatha C, Selvathi D (2016). Fpga implementation of road network extraction using morphological operator. Image Anal Stereol 35:93-103.

Vaideliene G, Valantinas J (2016). The use of haar wavelets in detecting and localizing texture defects. Image Anal Stereol 35:195-201.

Vezzetti E, Speranza D, Marcolin F, Fracastoro G (2016). Diagnosing cleft lip pathology in 3d ultrasound: A landmarking-based approach. Image Anal Stereol 35:53-65.

Wirjadi O, Schladitz K, Easwaran P, Ohser J (2016). Estimating fibre direction distributions of reinforced composites from tomographic images. Image Anal Stereol 35:167-79.

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Published

2017-03-31

How to Cite

Kreft, M. (2017). RESEARCH HIGHLIGHTS IN IAS. Image Analysis and Stereology, 36(1), 1–3. https://doi.org/10.5566/ias.1731

Issue

Section

Editorial

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