The use of mathematical morphology in image enhancement

Song, Jisheng; Stevenson, Robert Louis; Delp, Edward J.

doi:10.1109/mwscas.1989.101796

Cited by 10 publications

(6 citation statements)

References 22 publications

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“…Update the velocities V i of particle i using Equation (2) Update the position of particles using Equation (3) end for % Start of five successive mutations on Leader % Gaussian mutation It is wise to mention here that the green channel of the retinal image shows better vessel-background contrast and is therefore often employed for vessel segmentation and disease identification. In this work, the green channel is enhanced using the transformation function given in Equation (5). The flow chart of the proposed method is shown in Figure 2.…”

Section: Pseudocodementioning

confidence: 99%

An optimal statistical feature‐based transformation function for enhancement of retinal images using adaptive enhanced leader particle swarm optimization

Mahapatra

Agrawal

2022

Int J Imaging Syst Tech

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Retinal images play a crucial role in the clinical diagnosis and detection of many eye diseases. However, the retinal image is degraded with noise and suffers from low contrast, which makes it difficult to interpret the image precisely and accurately. So retinal image enhancement becomes a vital step before any further processing. Here, a new approach is suggested for fundus image enhancement, where the image is processed in the spatial domain through an optimal statistical feature‐based transformation function (SFTF). The proposed SFTF has four tunable parameters. An optimal set of these parameters is obtained through a newly suggested adaptive enhanced leader particle swarm optimization technique. The suggested method is investigated with freely accessible DRIVE, STARE, and IDRiD databases. The efficiency of the suggested technique is assessed through different validation indices. The results reveal superior performance compared with other popular methods used for vessel enhancement.

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Section: Pseudocodementioning

confidence: 99%

An optimal statistical feature‐based transformation function for enhancement of retinal images using adaptive enhanced leader particle swarm optimization

Mahapatra

Agrawal

2022

Int J Imaging Syst Tech

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“…Most research in Arabic handwriting has been done in the pre-processing stage and focused on baseline detection and skew correction as in [23], [24], [25]. A deep discussion for mathematical morphology algorithms that enhance images performing before recognition discoursed in [26].…”

Section: Morphological Operatorsmentioning

confidence: 99%

Off-Line Arabic Handwritten Words Segmentation using Morphological Operators

AbdAllah¹,

Viriri²

2020

SIPIJ

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The main aim of this study is the assessment and discussion of a model for hand-written Arabic through segmentation. The framework is proposed based on three steps: pre-processing, segmentation, and evaluation. In the pre-processing step, morphological operators are applied for Connecting Gaps (CGs) in written words. Gaps happen when pen lifting-off during writing, scanning documents, or while converting images to binary type. In the segmentation step, first removed the small diacritics then bounded a connected component to segment offline words. Huge data was utilized in the proposed model for applying a variety of handwriting styles so that to be more compatible with real-life applications. Consequently, on the automatic evaluation stage, selected randomly 1,131 images from the IESK-ArDB database, and then segmented into sub-words. After small gaps been connected, the model performance evaluation had been reached 88% against the standard ground truth of the database. The proposed model achieved the highest accuracy when compared with the related works.

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“…The operations like erode and dilate are applied on background subtracted images. Erode is used for removing noises in an image sequence and dilate for enlarging the boundaries of foreground regions in an image sequence [12].…”

Section: Introductionmentioning

confidence: 99%

Use of Multiple Thresholding Techniques for Moving Object Detection and Tracking

Vijayalakshmi¹,

Durairaj²

2013

IJCA

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The present work proposes many threshold techniques for moving object detection and tracking system. It applies more than one threshold techniques during segmentation phase of the work. Object detection is done by background subtraction with Alpha method and object tracking is carried out by feature point tracking approach. It is observed that Otsu threshold method seems to have produced a perfect extraction and yielded good result in moving object tracking. The results of applying multiple thresholds are reported in this paper.

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The use of mathematical morphology in image enhancement

Abstract: This paper discusses several nonlinear filtering algorithms based on mathematical morphology. The structure and properties of these filters are discussed and examples of the typical performance of these filters are given.

Cited by 10 publications

References 22 publications

An optimal statistical feature‐based transformation function for enhancement of retinal images using adaptive enhanced leader particle swarm optimization

An optimal statistical feature‐based transformation function for enhancement of retinal images using adaptive enhanced leader particle swarm optimization

Off-Line Arabic Handwritten Words Segmentation using Morphological Operators

Use of Multiple Thresholding Techniques for Moving Object Detection and Tracking

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