Implementation of Hough Transform for image processing applications

Chandrasekar, L.; Durga, G.

doi:10.1109/iccsp.2014.6949962

Cited by 16 publications

(5 citation statements)

References 5 publications

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“…However, if the line is vertical the m value is infinite makes the slope parameter for vertical line is not defined. Therefore, the in generalized Hough transform the (x, y) space is converted into (ρ, θ) space using (8) [23].…”

Section: Stair Detectionmentioning

confidence: 99%

Audible Obstacle Warning System for Visually Impaired Person Based on Image Processing

Yulianto,

Ma'muriyah,

Lina

2023

JNTE

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To be able to do their daily activities, a visually impaired person needs a guidance device to help him/her walk including to avoid obstacles on their way to the destination. The quick and clear instruction is given to the user is the most challenging problem to be solved. The visually impaired person should have simple guidance about the obstruction in front of him/her. Most guidance devices use simple sounds to give the warning without information about which direction the user should go. In this paper, an obstacle warning system based on image processing methods was developed. A guidance device for visually impaired persons using a single-board computer based on an image-processing algorithm has been designed. The main sensor of the guidance device is a NoIR camera. The distance measurement approximation model was developed with errors up to 4.3%. The test found that the proposed system can detect obstruction in the form of a person, the device also detects the stairs. The best detection obtains when the object position is less than 300 cm in front of the user. The stair detection was carried out by using the Hough line transform method. The output of the system is the sound of direction that can be heard through the headset.

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Section: Stair Detectionmentioning

confidence: 99%

Audible Obstacle Warning System for Visually Impaired Person Based on Image Processing

Yulianto,

Ma'muriyah,

Lina

2023

JNTE

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“…Arka planı temizlenen görüntüde sadece ray ve silinmemiş olan gürültüler mevcuttur. Bu görüntüye Hough dönüşümü uygulanarak rayın eğimi ve ortalama eğim değeri hesaplanmıştır [12]. Ray görüntüsü, hesaplanan ortalama eğim değeri kadar eğimin tersi yönünde döndürülerek rayın düz ve eğimsiz bir hale getirilmesi sağlanmıştır.…”

Section: öNeri̇len Yöntemunclassified

Detection of rail faults using morphological feature extraction based image processing

Taştimur

Akın

Karaköse

et al. 2015

2015 23nd Signal Processing and Communications Applications Conference (SIU)

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tr 2, 3, 4Özetçe -Demiryolu ulaşımında raydaki arızaların tespit edilmesi büyük öneme sahiptir. Raylarda oluşan arızalar güvenlik, ulaşımın aksaması ve maliyet gibi sorunların oluşmasına neden olur. Bu çalışmada demiryolu raylarında oluşan arızaları tespit etmek için morfolojik özellik çıkarımını kullanan görüntü işleme tabanlı algoritma önerilmektedir. Alınan ray görüntülerine görüntü işleme yöntemleri ve Hough dönüşümü uygulanarak ray tespit edilir. Tespit edilen ray görüntülerine morfolojik işlemlerin uygulanmasıyla görüntüdeki bölgelerin özellikleri çıkarılır ve arızalı olan bölgeler tespit edilir. Önerilen yöntem ile raydaki baş kontrolü, kırılma, apletilik ve ondülasyon arızaları tespit edilir. Bu çalışmada farklı yön ve ışıklandırma koşulları altındaki demiryolu rayı görüntüleri üzerinde önerilen yöntemin bütün adımları gerçekleştirilerek çalışma süresi düşük ve başarı oranı yüksek sonuçlar elde edilmiştir.Abstract -Determining the rail's breakdown has a big importance in railway access. The breakdowns of rails bring about problems such as insecurity, delay of access, and expenditure. In this work, in order to determine the breakdowns of rails using Morphological feature extraction based image processing algorithm is offered. The rail is determined through applying the image processing methods and Hough transform to the received images of rail. Headcheck breakage, apletilik and undulation of defects are determined by proposed method. Faulty regions is determined through extracting features of regions in images by applying Morphological operations to detected rail images. In this work, all steps of the offered method is applied to the images of rail under different direction and lighting, and with maximum accuracy and minimum working time, the results are acquired.

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“…After rail track lines are detected by using Hough transform [28,29], the intersection of two straight rail lines in the image can be computed. To compute vanishing point, common form of a linear equation can be used.…”

Section: Switch Detection Methodsmentioning

confidence: 99%

“…The connected components have been detected to extract rail track from the railway image. After rail track is labelled on image, rail lines have been founded by utilizing Hough transform [28,29]. Hough transform returns lines that have different lengths.…”

Section: Switch Detection Methodsmentioning

confidence: 99%

A Vision Based Condition Monitoring Approach for Rail Switch and Level Crossing using Hierarchical SVM in Railways

Taştimur

Karaköse

Akın

2016

International Journal of Applied Mathematics, Electronics and Computers

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Rail track, turnout and level crossing are critical parts of railway components. So faults of rail surface are directly related to the operation safety. The defects occurring in switches can lead to accidents and the derailment of the train. Therefore, it is necessary to utilize advanced technology to monitor rail damage of the switch and level crossing zones. In this study, the switch and level crossing detection are performed with vision based contactless image processing techniques. Edge detection algorithm, image processing filters, morphological feature extraction, Hough transform and hierarchical SVM classifier are utilized to detect turnout and level crossing regions in the railway images. While switch points are detected, images of the area in front of the train are continuously taken from camera placed on the train. These images contain foreign objects such as buildings, trees, etc. The foreign objects existing in the railway image make it difficult to detect accurately the rail track. The turnout and level crossing detection cannot also be performed using the information of the rail track that cannot be correctly detected. The several processes, such as some image processing filters and morphological feature extraction, have been performed to solve this problem. With destroying the foreign objects from the railway images, both the accuracy rate of the proposed method has been increased and real-time implementation of the method is provided. The Hough transform is utilized to detect rail track, switch and level crossing in the proposed method. The turnout detection is performed by applying SVM classifier to railway image. The proposed method provides real-time rail track, level crossing and turnout detection. Furthermore, this method has gained dynamic feature due to not be utilized any template image for switch detection. When evaluated from these aspects, both the proposed method is superior to other methods in literature and results were obtained in a shorter time thanks to applying ROI Segmentation to the railway image.

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Implementation of Hough Transform for image processing applications

Cited by 16 publications

References 5 publications

Audible Obstacle Warning System for Visually Impaired Person Based on Image Processing

Audible Obstacle Warning System for Visually Impaired Person Based on Image Processing

Detection of rail faults using morphological feature extraction based image processing

A Vision Based Condition Monitoring Approach for Rail Switch and Level Crossing using Hierarchical SVM in Railways

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