Structuring element

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

Plastic bottle shape classification using partial erosion-based approach

Abstract: In this paper, a work on representing plastic bottle shape using erosion based approach for an automated classification is reported. Morphological operations are used to describe the structure or form of an image. By using the two-dimensional description of plastic bottle silhouettes, edge detection of the object silhouette is performed followed by the erosion process. This work will compare two versions of erosion which are regular erosion, the Matlab function imerode and the improved version of erosion which is called partial erosion. Normalization procedure in which the sum pixel value after erosion is divided by the sum pixel of the whole silhouette is done. The normalized values are grouped into histograms of 9 bins of sum pixel value(9HbSPV), find its maximum number to form as a feature set and is then used as inputs to train a neural network for plastic bottle shape classification. Results obtained showed that the proposed feature extraction method can be applied to discriminate plastic bottles according to shape, either slim or broad bottles, efficiently.

Adaptive pattern spectrum image description using Euclidean and Geodesic distance without training for texture classification

Abstract: Mathematical morphology can be used to extract a shape-size distribution called pattern spectrum (PS) with texture description purposes. However, the structuring element (SE) used to compute it does not vary along the image; and therefore it does not capture its geometrical variations. The author-s proposal consists of computing an SE at each pixel whose size and shape varies with two distance criterions: an Geodesic distance and a Euclidean distance, in order to fit the texture as well as possible. Combining the Geodesic and the Euclidean descriptors as just one descriptor, the classification results of several textures from the VisTex and Brodatz database show that this approach outperforms the classical PS, the Geodesic and the Euclidean descriptors separately and, in contrast with other adaptive methods, it does not require previous training.

Retinal blood vessel segmentation using morphological structuring element and entropy thresholding

Abstract: An automated segmentation method for Retinal blood vessel extraction is developed. The method uses Morphological structuring element and basic filters for preprocessing. The preprocessing step enhances and makes the retinal images most suitable for vessel extraction. Thresholding technique is employed to extract the blood vessels from the background image. This method is evaluated on the two publicly available data bases namely STARE and DRIVE database. This method is compared with the matched filter method for segmentation and kirsch template method. Our method gives appreciable blood vessel extraction as compared with other methods.

Fingerprint Thinning Algorithm Based on Mathematical Morphology

Abstract: Thinning plays an important role in automatic fingerprint identification system (AFIS). This paper applies hit-miss transform which is based on mathematical morphology to fingerprint thinning, It proposes a new view on thinning algorithm based on the transform, and improves structuring element on the ground of predecessor's research, getting improved thinning effect.