Rudolf Schraml

Temporal and longitudinal variances in wood log cross-section image analysis

In this work two practical issues of biometric log recognition using log end images are investigated: Temporal and longitudinal variances of log cross-sections (CSs). These variances are related to the requirement of robustness for biometric characteristics. A texture feature-based fingerprint matching technique is used to compute matching scores between CS images. Our experimental evaluation is based on the temporal and longitudinal variances of 35 slices of a single tree log which where captured at four time delayed sessions. Results indicate, that biometric log recognition using log end images is robust and is able to overcome both issues. This work contributes to the development of a biometric log recognition system by showing that a texture feature-based matching technique is applicable to log CSs.

PITH ESTIMATION ON ROUGH LOG END IMAGES USING LOCAL FOURIER SPECTRUM ANALYSIS

The location of the pith is an important feature of cross sections from tree logs. Images of log ends can be taken at little cost and at almost every stage in the log processing chain. Analysing images of rough log ends automatically requires robust pith estimation. This work evaluates two pith estimation algorithms using four different local Fourier Spectrum analysis methods. Proving that size, selection and amount of annual ring sections have an impact on both algorithms, this work contributes to existing literature. In comparing experiments for pith estimation for digital images of rough log ends and computer tomography (ct) cross section images, this paper highlights the difficulties for pith estimation on rough log end images. Finally, our results show that peak analysis and principal component analysis for local Fourier Spectrum analysis achieve the best accuracy and timing performance for pith estimation on rough log end images.

Tree Log Identification Based on Digital Cross-Section Images of Log Ends Using Fingerprint and Iris Recognition Methods

Tree log biometrics is an approach to establish log traceability from forest to further processing companies. This work assesses if algorithms developed in the context of fingerprint and iris recognition can be transferred to log identification by means of cross-section images of log ends. Based on a test set built up on 155 tree logs the identification performances for a set of configurations and in addition the impacts of two enhancement procedures are assessed.

Validation and reliability of the discriminative power of geometric wood log end features

Recent investigations on biometric log recognition using end face images indicated that shape information is beneficial for the biometric system performance. This study assesses the discriminative power and reliability of geometric features which are computed by means of segmented cross-sections and their pith positions. The experimental evaluation is based on cross-section images from 150 different logs, for which the ground truth of the boundary and pith position is known. By assessing the verification performance for ground truth data and automated segmentation/ pith estimation procedures this work highlights the basic discriminative power of geometric log end features and further validates their reliability in case of using automated procedures.

Towards Drug Counterfeit Detection Using Package Paperboard Classification

Most approaches for product counterfeit detection are based on identification using some unique marks or properties implemented into each single product or its package. In this paper we investigate a classification approach involving existing packaging only in order to avoid higher production costs involved with marking each individual product. To detect counterfeit packages, images of the package’s interior showing the plain structure of the paperboard are captured. Using various texture features and SVM classification we are able to distinguish drug packages coming from different manufacturers and also forged packages with high accuracy while a distinction between single packages of the same manufacturer is not possible.

Towards the applicability of biometric wood log traceability using digital log end images

We introduce into biometric log recognition using digital log end images.We present investigations on the robustness to different longitudinal and surface cross-section variations.Results provide insights on the applicability in an industrial environment.We assess the discriminative power of the annual ring pattern, the shape and the fusion of both.Results show a high robustness to log length cutting using different cutting tools. Log traceability in the timber based industries is a basic requirement to fulfil economical, social and legal requirements. This work introduces biometric log recognition using digital log end images and explores the robustness to a set of log end cross-section (CS) variations. In order to investigate longitudinal and surface CS variations three tree logs were sliced and captured in different sessions. A texture feature-based technique well known from fingerprint recognition is adopted to compute and match biometric templates of CS images captured from log ends. In the experimental evaluation insights and constraints on the general applicability and robustness of log end biometrics to identify logs in an industrial application are presented. Results for different identification performance scenarios indicate that the matching procedure which is based on annual ring pattern and shape information is very robust to log length cutting using different cutting tools. The findings of this study are a further step towards the development of a biometric log recognition system.

Privacy enhancing technologies in video surveillance applied to JPEG2000 codestreams

Privacy enhancing technologies in video surveillance are discussed for JPEG2000 codestreams. Protection accuracy, compression impact, and computational requirements are assessed and compared. Recommendations are given which approach is favourable under certain conditions.

Real or Fake: Mobile Device Drug Packaging Authentication

Shortly, within the member states of the European Union a serialization-based anti-counterfeiting system for pharmaceutical products will be introduced. This system requires a third party enabling to track serialized and enrolled instances of each product from the manufacturer to the consumer. An alternative to serialization is authentication of a product by classifying it as being real or fake using intrinsic or extrinsic features of the product. Thereby, one approach is packaging material classification using images of the packaging textures. While the basic feasibility has been proven recently, it is not clear if such an authentication system works with images captured with mobile devices. Thus, in this work mobile drug packaging authentication is investigated. The experimental evaluation provides results on single- and cross-sensor scenarios. Results indicate the principal feasibility and acknowledge open issues for a mobile device drug packaging authentication system.

On rotational pre-alignment for tree log identification using methods inspired by fingerprint and iris recognition

Tree log end biometrics is an approach to track logs from forest to further processing companies by means of log end images. The aim of this work is to investigate how to deal with the unrestricted rotational range of cross sections in log end images. Thus, the applicability of three different rotational pre-alignment strategies in the registration procedure is assessed. Template computation and matching is based on fingerprint and iris recognition techniques which were adopted and extended to work with log end images. To address these questions, a testset built up on 279 tree logs is utilized in the experiments. The evaluation assesses the basic performance of the rotational pre-alignment strategies and their impact on the verification and identification performances for different fingerprint- and iris-based configurations. Results indicate that rotational pre-alignment in the registration procedure is the main component to deal with rotation in log end biometrics. The best configurations achieve identification rates