Semi-automated analysis of dot blots using ImageJ/Fiji

Commercially available dot blots provide a set of specific antibodies spotted on membranes in a given pattern. If the target analyte is present in the solution that the membrane is incubated with, the detection reaction will result in a chemiluminescence signal which is recorded by film or scanner. In order to know which analytes were detected, the analysis consists of measuring the intensity of the recorded signal on each spot. Manually measuring the entire array (typically ~200 spots) is unreliable and tedious. Fully automatic registration of the blot membrane to the template pattern often fails since there might be only very few positive spots on the membrane. This article presents an ImageJ/Fiji macro that requires minimal user input to perform a robust iterative registration of an adjustable template mask representing the spot pattern to the recorded blot. Once the template mask is matched to the dot blot, the spot intensity of each dot is measured and reported in a results table.

A Robust and Versatile Pipeline for Automatic Photogrammetric-Based Registration of Multimodal Cultural Heritage Documentation

Imaging techniques and Image Based-Modeling (IBM) practices in the field of Cultural Heritage (CH) studies are nowadays no longer used as one-shot applications but as various and complex scenarios involving multiple modalities; sensors, scales, spectral bands and temporalities utilized by various experts. Current use of Structure from Motion and photogrammetric methods necessitates some improvements in iterative registration to ease the growing complexity in the management of the scientific imaging applied on heritage assets. In this context, the co-registration of photo-documentation among other imaging resources is a key step in order to move towards data fusion and collaborative semantic enrichment scenarios. This paper presents the recent development of a Totally Automated Co-registration and Orientation library (TACO) based on the interoperability of open-source solutions to conduct photogrammetric-based registration. The proposed methodology addresses and solves some gaps in term of robustness and versatility in the field of incremental and global orientation of image-sets dedicated to CH practices.

A workpiece registration and localization adjustment method with contact inspection under multi-tolerance conditions

The workpiece contour errors from previous process affect current process. In order to improve workpiece allowance distribution, this article presents a workpiece registration and localization adjustment method with contact inspection. According to the analysis of machining deviation, the rotational and translational registration matrixes from multi-tolerance surfaces to workpiece are obtained by surface characteristic and translational vectors. The workpiece localization (position and orientation) adjustment can be realized by transforming coordinate systems of 5-axis machine tool. Through adaptive and iterative registration and adjustment, the optimized workpiece localization for current process is obtained. The experimental results show that the method can improve allowance uniformity effectively.

An Iterative Method for 3D Body Registration Using a Single RGB-D Sensor

In this paper, the problem of 3D body registration using a single RGB-D sensor is approached. It has been guided by three main requirements: low-cost, unconstrained movement and accuracy. In order to fit them, an iterative registration method for accurately aligning data from single RGB-D sensor is proposed. The data is acquired while a person rotates in front of the camera, without the need of any external marker or constraint about its pose. The articulated alignment is carried out in a model-free approach in order to be more consistent with the real data. The iterative method is divided in stages, contributing to each other by the refinement of a specific part of the acquired data. The exploratory results validate the proposed method that is able to feed on itself in each iteration improving the final result by a progressive iteration, with the required precision under the conditions of affordability and unconstrained movement acquisition.