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1. #SEM IMAGE CALIBRATION IN JMICROVISION REGISTRATION#
2. #SEM IMAGE CALIBRATION IN JMICROVISION SOFTWARE#

The parallel projection (typically orthographic projection) corresponds to a perspective projection with an infinite focal length. The perspective projection, where objects are projected towards a point (the center of projection), is used in classical camera models. The projection model relates a 3-D point on a specimen in the observed space to its projection in the 2-D image. Several photogrammetric related calibration methods have been proposed for three dimensional imagery and reconstruction in SEM. In earlier studies, photogrammetric analysis of SEM has been considered by some authors. It has been demonstrated that accurate SEM calibration and error analysis was one of the major problems when considering such sensor. Since the structure of a scanning electron microscope is very different from the structure of an optical microscope, it became apparent that novel image analysis, geometrical projection models and calibration processes would be necessary in order to extract accurate information from the SEM images. Constraints are provided by the scene rigidity in this approach. Alternatively, another technique, called self-calibration, do not use any calibration pattern but the parameters are estimated by moving a camera in a static scene. In earlier studies, a linear estimation of some parameters is considered and the others are estimated iteratively.

It consists in minimizing the error between the observation and the forward-projection of the model. Other techniques use non-linear optimization methods. Some authors use linear techniques, where least squares method is employed to estimate the intrinsic parameters and the pose (i.e., the position and the orientation of the calibration pattern frame in the sensor frame).

#SEM IMAGE CALIBRATION IN JMICROVISION REGISTRATION#

This issue is usually considered as a registration problem. The goal of the calibration process is to determine the set of parameters which define the relationship between the three-dimensional (3-D) coordinates of an object point on the observed specimen and its projection in the image plane (such parameters that include, in an optical system, the focal length, the dimension of pixel, the location of principle points on the image plan are named intrinsic parameters). When the task requires the computation of metric information from the acquired two-dimensional (2-D) images, the calibration of the SEM is an important issue to be considered.Ĭalibration of an optical sensor has been widely investigated over the last decades. This is an essential instrument to display, measure and manipulate the micro and nano-structure with a micrometers or nanometers accuracy.

Quantify components: objects or background.

Read images in TIFF, BMP, GIF, JPEG, PNG, and PNM formats.

#SEM IMAGE CALIBRATION IN JMICROVISION SOFTWARE#

This software has been specially developed for the analysis of high definition images of thin rock sections, but it can easily be used in other fields. Moreover, the magnifying lens and the multiview tool allow a simultaneous view of several images, each one having its own zoom coefficient while maintaining a common position in the center. Like a microscope, it allows a dynamic observation of a specimen with the possibility of combining various focus or modes of lighting (polarized light, fluorescence.). JMicroVision contains tools with different degrees of automation to manage complex and varied images. It has an intuitive user interface with powerful features and supports very large images. JMicroVision has been designed to describe, measure, quantify and classify components of all kinds of images. User-friendly software for analyzing large images