RESEARCH HIGHLIGHTS IN IAS

• Main Author: Marko Kreft
• Format: Article
• Language: English
• Published: Slovenian Society for Stereology and Quantitative Image Analysis 2017-03-01
• Series: Image Analysis and Stereology
• Subjects: image analysis; stereology; computer vision; process modelling
• Online Access: https://www.ias-iss.org/ojs/IAS/article/view/1731
• ISSN: 1580-3139; 1854-5165

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.