Improved Mangrove Crown Measurement from Airborne Lidar Data using Marker-controlled Watershed Algorithm-filtered Hamraz Technique

Marasigan, Rufo I.; Festijo, Enrique D.; Juanico, Dranreb Earl; Medina, Ruji P.

doi:10.1109/icecie47765.2019.8974833

Cited by 5 publications

(1 citation statement)

References 61 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The segmentation results in the image using the morphological watershed and transformation watershed methods still contain noise. Segmentation using marker controlled watershed method (Girish et al, 2018;Marasigan Jr et al, 2019;Datta & Chaki, 2020;Mon et al, 2018). The results of segmentation using the marker watershed method still have an average accuracy below 92%.…”

Section: Related Workmentioning

confidence: 99%

A New Watershed Algorithm for Pothole Image Segmentation

Indriyani¹,

Utoyo²,

Rulaningtyas³

2021

STUD INFORM CONTROL

View full text Add to dashboard Cite

The road casualties caused by poor road conditions, especially potholed roads, amount to a high percentage of 13% per year in Asia. In order for the government to carry out repair works, they must know the surface area of the potholed road, the depth of the potholes, and the position of the potholes. In this paper, with the purpose of determining the surface area of the potholed road, segmentation was carried out first. The segmentation method used here is a new watershed algorithm. This algorithm includes six processes: smoothing, calculating the gradient value, automatic determination of minimum flooding value, combining the catchment basins, erasing the remaining watershed lines, and creating a watershed curve. The proposed algorithm is evaluated and compared with previously analysed watershed segmentation methods. This study shows that this algorithm is effective for reducing the effects of excessive segmentation. The proposed algorithm obtained a high accuracy of 95.34%, which is higher than that of the existing watershed segmentation methods.

show abstract

Section: Related Workmentioning

confidence: 99%