Structuring element

About: Structuring element is a research topic. Over the lifetime, 997 publications have been published within this topic receiving 26839 citations.

Extraction of Fine Blood Vessels from an Ultrasound Image by an Image Processing

Abstract: This paper discusses some useful image processing techniques for an ultrasound image using adaptive morphological operations. They are defined in such a way that the used structuring element is a function of local image to respond its characteristics. The defined mathematical morphology has almost the same mathematical structure and properties as the conventional one. Besides, the former has an advantageous image processing to others. For example, this technique to ultrasound images to extract blood vessel and showed its useful function. We discussed parameter evaluation and setting, from a statistical point of view. Experimental results are also demonstrated.

Soft morphological structuring element decomposition

Abstract: In this paper a decomposition technique suitable for any grey-scale soft morphological structuring element is presented. A hardware structure implementing this technique is also presented.

Microarray spot detection using flat structuring periodic line and specific distance shaped morphology

Abstract: Microarray is one of the most recent and important technology for exploring the genome [1,2]. Image analysis is an important role of microarray experiments, one, which can have a potentially large impact on subsequent analysis such as clustering or the identification of differentially expressed genes [3]. Microarray image grid and spot position determination is a very important step in the analysis of microarray image because it is the first part we need to do for the analysis. By comparing gene expression in normal and abnormal cells, microarrays may be used to identify genes, which are involved in particular diseases. These genes may then be targeted by therapeutic drug. Making this part automated and fast is also important. So we consider this as indeed problem of spot detection and overcome it by using flat structuring element disk-diamond shaped morphological technique, which gives satisfied results. And also we compare the original &resultant image results on the basis of image quality measure [4]. KeywordsMicroarray, flat structuring element, morphology, segmentation, spot detection

Morphological approach for detection of protein spots from 2D-gel image

Abstract: The present paper on detection of Protein spots from 2D gel image used several morphological operators. Protein spots are associated mostly with those regions whose intensity is least in 2D gel images. As maximum protein spots are in round shape, a disk shape structuring element is used for identification. More number of protein spots is presents in complex region of 2D gel image. For detecting more number of protein spots from 2D gel image, radius of structuring elements are taken care up in this paper.

Mathematical Morphology based Image Enhancement and Background Detection

Abstract: This paper deals with analysis of image Intensification carried out various methodologies used in Mathematical Morphological (MM) theory on poor lighting images. In this paper, Some Morphological Transformation have been processed through Block Analysis, Morphological Operation and Opening by Reconstruction on dark Images. Basically, Image enhancement and Background detection is illustrated through Weber's Law Operator. Weber Law consists of two operators as block analysis while second operator utilize opening by reconstruction to define multi background notion. Such Morphological operations are Erosion, Dilation, Composite operation such as Opening and Closing. In Mathematical Morphology there is transformation that allows filtering of the Image with new contour leads to Opening by reconstruction and closing by reconstruction as well. Analysis of above mention methods illustrated through the processing of images with filtering techniques along with different dark background images.