The objective of semantic segmentation in microscopic images is to extract the cellular, nuclear or tissue components. This problem is challenging due to the large variations of features of these components (size, shape, orientation or texture). In this paper we present an overview of the proposed segmentation techniques for microscopic images. This is not a comprehensive study, but rather an a...

We present an approach for significantly improving the quantitative analysis of motion in noisy fluorescence microscopic image sequences. The new partial differential equation based method is a general extension of a 2-D nonlinear anisotropic diffusion filtering scheme to a specially adapted 3-D nonlinear anisotropic diffusion filtering scheme, with two spatial image dimensions and the time t i...

Water flooding microscopic seepage experiment is an effective method to study the microvadose mechanisms as well as the distributions of remaining oil. Throughout the experiment the quantitative description of the porous medium fluid flow parameters such as porosity, oil saturation and so forth is crucial. A quantitative analysis method is proposed via image processing, including image preproce...

Traditional methods of chromite exploration are mostly based on geophysical techniques and drilling operations. They are expensive and time-consuming. Furthermore, they suffer from several shortcomings such as lack of sufficient geophysical density contrast. In order to overcome these drawbacks, the current research work is carried out to introduce a novel, automatic and opto-geometric image an...

Image Enhancement is the first and foremost step that has to be done in all image processing applications. It is used to improve the quality of digital images. Microscopic images are prone to addition of noise from various sources such as error in camera calibration, excess staining of microscopic slides, etc.; Image de-noising is an enhancement technique that is used to remove noise present in...

New imaging technologies allow the acquisition of in vivo and in situ microscopic images at the cellular resolution in any part of the living body. The automated analysis of these images raises specific issues which require the development of new image processing techniques. In this work, we present some of these issues, and describe some recent advances of microscopic image processing, in part...

Microscopic images in material science documents have increased number due to the growth and common use of electron microscopy instruments. Through data mining techniques, they are easily accessible can be obtained from published online. As data-driven approaches becoming increasingly field, massively acquired experimental through play important roles terms developing an artificial intelligence...

Texture classification can be concluded as the problem of classifying images according to textural cues, that is, categorizing a texture image obtained under certain illumination and viewpoint condition as belonging to one of the pre-learned texture classes. Therefore, it would mainly pass through two steps: image representation or description and classification. In this paper, we focus on the ...