Computers and Electronics in Agriculture / Towards the applicability of biometric wood log traceability using digital log end images

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.(VLID)223160

Improving CT image analysis of augmented bone with raman spectroscopy

In recent years, bone graft substitutes have been increasingly used in the medical field, for example, in order to promote new bone formation. Microcomputed tomography (-CT) is an image-guided technique used in medicine as well as in materials science, enabling the characterization of biomaterials with high spatial resolution. X-ray-based methods provide density information; however, the question how far conclusions on chemical structures can be inferred from any kind of CT information has not been intensively investigated yet. In the present study, a bone sample consisting of autogenous bone derived cells (ABCs) and bovine bone mineral (BBM) was investigated by -CT and Raman spectroscopic imaging, that is, by two nondestructive imaging methods. Thereby, the image data were compared by means of regression analysis and digital image processing methods. It could be found that 51.8% of the variance of gray level intensities, as a result of -CT, can be described by different Raman spectra of particular interest for bone composition studies by means of a multiple linear regression. With the better description of -CT images by the linear model, a better distinction of different bone components is possible. Therefore, the method shown can be applied to improve CT-image-based bone modeling in the future