Digital Imaging

Abstract

This article reviews the main theoretical and practical aspects of sequence normally followed in digital image-acquisition, processing, analysis, and output for material characterization. It discusses the main methods of digital imaging, image processing, and analysis, as applied to microscopy of materials. The article describes the basic concepts of sampling and resolution and quantization of light microscopy, scanning electron microscopy, and transmission electron microscopy. It discusses the acquisition of a digital image that accurately represents the sample under observation and output of the image to a printer. The methods used to enhance the digital image and to extract quantitative information are also described. Different types of image segmentation, namely, adaptive segmentation and contour-based segmentation, are reviewed. The article also presents case studies on the application of image processing and analysis to materials characterization.

Characterization of Fly Ash and a Protective Coating for Brazilian Thermal Power Plant Boilers

“…Fiji (Image J) software 34 was used for the extraction of image attributes. After segmentation in binary images to separate the image objects of interest from the background, the defect fraction was calculated by the ratio of dark tones and selected square area 35 . Figure 1 exemplifies one of images used and its respective histogram (left and above) generated for quantification process.…”

Untitled

“…A sequence of processing steps and digital image analysis was developed in Axiovison 4.8 software (Carl Zeiss) and applied to the digital images of the deformed pipes at the end of each test. This sequence consisted of segmentation, post-processing and measurement steps [12]. In the segmentation step the image was binarized by a manual selection of color shades (yellow) separating the object of interest (the pipe) from the rest of the image (the background), as shown in Figure 3a & 3b.…”

“…A post-processed final image is shown in Figure 3c. Details on these steps of digital image analysis are described in other works [12,13]. From the post-processed image, it is possible to measure the geometric parameters that characterize the deformation process of a pipe [10].…”

Classificação Automática De Hematita Especular E Hematita Porosa Em Pellet Feed Por Análise Digital De Imagens

“…A rotina de análise de imagens segue a chamada seqüência padrão: préprocessamento, segmentação, pós-processamento, extração de atributos e classificação (4) As imagens adquiridas ao microscópio (Figura 1) são inicialmente pré-processadas para correção de background e normalização de contraste. Em seguida, a fase hematita é identificada e discriminada através de uma sub-rotina de segmentação automática.…”