Structuring element

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

Grey-scale 1-d dilations with spatially-variant structuring elements in linear time

Abstract: Spatially variant morphological operators can significantly improve filtering capabilities or object detection score of various applications. Whereas an effort has been made to define the theoretical background, the efficient implementation of adaptable algorithms remained far less considered. In this paper, we present an efficient, one-scan, linear algorithm for 1-D grey-scale dilations/erosions with spatially variant structuring elements. The proposed algorithm processes data in stream, can work in place and produces results with minimal latency. The computing time is independent of the structuring element size.

New Alternating Sequential Filters and the application for impulsive noise removal

Abstract: Alternating Sequential Filters (ASFs) are important composing operations of mathematical morphology in different applications. However, because of the image detail smoothing of the opening and closing operations in ASFs, ASFs can not perform very well. New top-hat transform had been proposed through reconstructing the used structuring elements, which can protect image details. And, the main operations in new top-hat transform can achieve the same purpose of opening or closing for bright or black feature extraction. In light of this, a new class of ASFs based on new top-hat transform is proposed in this paper. An application of impulsive noise suppression is used to show the efficient performance of new ASFs. Experimental results show that new ASFs perform better than ASFs, and can be widely used in different applications.

An adaptive morphological algorithm to segment Chinese square seal in bank check image

Abstract: In this paper, an adaptive morphological segmentation algorithm is proposed to extract a binary Chinese square seal from a bank check image. The grayscale Chinese square seal is extracted from the color bank check image according to the color information. Different Chinese characters have different stroke features and background evenness. To process each character in the square seal respectively, the extracted square seal is divided into four sub-squares. The background across each sub-square of the grayscale seal image is smoothed by top-hat transformation. The size of structuring element in top-hat transformation might have a great influence on the segmentation. The optimal size of the structuring element for the top-hat transformation on each sub-square is iteratively estimated according to the local foreground area. Each top-hat processed sub-square is binarized by Otsu's method. In each binary sub-square, holes smaller than a threshold are filled which is proportional to the ratio of the foreground area to the area of the whole sub-square. The experiment result shows that the proposed algorithm can correctly segment Chinese characters with intricate and dense strokes in a bank check square seal. Adhesion and incompleteness distortions in the segmentation results are reduced, even when the original square seal has a poor quality.

Word bounding box detection

Abstract: A system for determining bounding boxes includes the input interface and a processor. The input interface is configured to receive an image. The processor is configured to detect a line associated with connected components in the image; determine gap sizes within the line; determine a word structuring element size using the gap sizes; and determine bounding boxes for the line based at least in part on the word structuring element size.

Toward the Optimal Decomposition of Arbitrarily Shaped Structuring Elements by Means of a Genetic Approach

Abstract: The decomposition of a binary morphological structuring element is a well-known problem that has often been addresses in the literature. This work present a new approach based on an Evolution Program: using an iterative stochastic technique, it allows to determine the optimal decomposition of an arbitrarily shaped binary morphological structuring element into the shortest chain of elementary factors chosen from a given set.