Research of lane detection and recognition technology based on morphology feature

Wang, Jian; Sun, Shaozeng; Gong, Jing-Chao; Yu, Cao

doi:10.1109/ccdc.2013.6561616

Cited by 5 publications

(2 citation statements)

References 5 publications

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“…The results show that algorithm has high resistance to noise and retain better edges for color road image edge detection than the traditional algorithms. [6] found that when selected seed points are correct, the accuracy of the method of road region extraction based on regional growth is high. This method can identify lane region exactly.…”

Section: Chan Yee Low Et Al (2014) [2]mentioning

confidence: 99%

Curved Lane Detection using Improved Hough Transform and CLAHE in a Multi-Channel ROI

Kaur¹,

chhabra²

2015

IJCA

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With the increase in advent of intelligent vehicle technology, LDWS technique is actively developing to provide assistance to drivers in generating warning signal in case of lane departure. In this paper, the input image is divided into four regions of interest. Then the CLAHE is applied on the given ROI for better image contrast and removal of noise using gradient filter. Improved Hough Transform is applied on the given image for the detection of curved and straight lanes. After detecting the lanes, they are colored with green color so that they are clearly visible. The proposed algorithm is analysed based on the parameters like Accuracy, BER, Fmeasure, and Sensitivity. The analysis shows that this algorithm provides efficient and effective performance compared to the existing algorithm.

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Section: Chan Yee Low Et Al (2014) [2]mentioning

confidence: 99%

Curved Lane Detection using Improved Hough Transform and CLAHE in a Multi-Channel ROI

Kaur¹,

chhabra²

2015

IJCA

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“…Guaranteeing outcomes were obtained with high overall performance of detection. Wang Jian et al 2013 [6] This specific paper draws attention on morphology characteristic of lane, studies lane recognition as well as extracts the actual parameters connected with identification of lane. All these factors are generally very essential for lane departure warning.…”

Section: Related Workmentioning

confidence: 99%

A Review on the Artificial Bee Colony & Clahe Based Hybrid Hough Transform For Efficient Lane Detection

Multani

Marwaha²

2017

IJECS

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This paper represents that lane coloration has become popular in real time vehicular ad-hoc system. Lane detection is normally helpful to localize path limits, determine undesired lane variations, and to enable approximation of the upcoming geometry of the road. There are different types of methods that are used for detecting lines, curves and ellipses i.e. hough transform, clustering and curve fitting. The overall objective of this paper is to providing better performance in lane coloration algorithm. The methods developed till now are working effectively as well as giving good results.

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Lane Detection for Self-Driving Cars Using AI

Banerjee,

Thakur,

Ambikesh

et al. 2023

2023 3rd Asian Conference on Innovation in Technology (ASIANCON)

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Research of lane detection and recognition technology based on morphology feature

Cited by 5 publications

References 5 publications

Curved Lane Detection using Improved Hough Transform and CLAHE in a Multi-Channel ROI

Curved Lane Detection using Improved Hough Transform and CLAHE in a Multi-Channel ROI

A Review on the Artificial Bee Colony & Clahe Based Hybrid Hough Transform For Efficient Lane Detection

Lane Detection for Self-Driving Cars Using AI

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