scholarly journals Drivable Road Corridor Detection using Flood Fill Road Detection Algorithm

2019 ◽  
Vol 9 (2) ◽  
pp. 5011-5014
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Detection Algorithm ◽  
Image Processing Technique ◽  
Road Detection ◽  
The Road ◽  
Detection Algorithms ◽  
Color Differences ◽  
On The Road ◽  
Flood Fill

Current image processing techniques for drivable road detection make use of lane markings. However, most roads lack lane markings which make such techniques obsolete. For such conditions, an image processing technique is required which identifies the boundaries of the road based on the color differences between the road and the surroundings. This paper proposes a flood fill road detection approach in which we first analyze a sample of the road and compute its RGB pixel distribution. The pixel range is used to detect the other road pixels in the image. Edge detection algorithms are then applied on the detected road to give road edge. It classifies the road on the basis of the visible differences between the road and its neighborhood. It allows for subtle color differences on the road surface, and unlike a color mask, due to the inherent growing nature of a flood fill algorithm, it does not detect neighborhood elements beyond the boundary having features similar to the road. This technique also manages to detect any obstructions on the road as opposed to other edge detection algorithms. We also propose methods to enable quick computation of otherwise expensive flood-fill algorithm. The method was tested on both marked and unmarked lanes and produced satisfying results for both images and videos.

scholarly journals Hardware Implementation of Sobel Edge Detection Algorithm

2020 ◽  
Vol 32 ◽  
pp. 03051
Author(s):  
Ankita Pujare ◽  
Priyanka Sawant ◽  
Hema Sharma ◽  
Khushboo Pichhode
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Feature Detection ◽  
Hardware Implementation ◽  
Software Tool ◽  
Detection Algorithm ◽  
Edge Detection Algorithm ◽  
Detection Algorithms ◽  
Sobel Edge Detection ◽  
Image Edges

In the fields of image processing, feature detection, the edge detection is an important aspect. For detection of sharp changes in the properties of an image, edges are recognized as important factors which provides more information or data regarding the analysis of an image. In this work coding of various edge detection algorithms such as Sobel, Canny, etc. have been done on the MATLAB software, also this work is implemented on the FPGA Nexys 4 DDR board. The results are then displayed on a VGA screen. The implementation of this work using Verilog language of FPGA has been executed on Vivado 18.2 software tool.

scholarly journals A Low Redundancy Wavelet Entropy Edge Detection Algorithm

2021 ◽  
Vol 7 (9) ◽  
pp. 188
Author(s):  
Yiting Tao ◽  
Thomas Scully ◽  
Asanka G. Perera ◽  
Andrew Lambert ◽  
Javaan Chahl
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Shannon Entropy ◽  
Detection Algorithm ◽  
Edge Detection Algorithm ◽  
Detection Techniques ◽  
Detection Algorithms ◽  
Real Time Image ◽  
Time Image ◽  
Vision Application

Fast edge detection of images can be useful for many real-world applications. Edge detection is not an end application but often the first step of a computer vision application. Therefore, fast and simple edge detection techniques are important for efficient image processing. In this work, we propose a new edge detection algorithm using a combination of the wavelet transform, Shannon Entropy and thresholding. The new algorithm is based on the concept that each Wavelet decomposition level has an assumed level of structure that enables the use of Shannon entropy as a measure of global image structure. The proposed algorithm is developed mathematically and compared to five popular edge detection algorithms. The results show that our solution is low redundancy, noise resilient, and well suited to real-time image processing applications.

Surface Image Edge Detection Algorithm Based on Grey Relational Analysis

2012 ◽  
Vol 461 ◽  
pp. 343-346 ◽  
Author(s):  
Gang Li ◽  
Ying Fang ◽  
Ya La Tong
Keyword(s):  
Edge Detection ◽  
Good Method ◽  
Detection Algorithm ◽  
Relational Model ◽  
Small Data ◽  
The Road ◽  
Image Edge Detection ◽  
Surface Image ◽  
Image Edge ◽  
Grey Relational

Automatic detection of pavement cracks is one of the very hot topics. For the characteristics of “small data, poor information” in the surface image processing, we construct ed a grey image relational model to characterize the local image edge feature, by selecting the appropriate threshold to extract the edge of appropriate level. Finally, simulation experiments show that the new algorithm can effectively improve the road edge detection results, and it is an effective good method worthy further study.

Real-time unstructured road detection based on CNN and Gibbs energy function

2021 ◽  
pp. 1-19
Author(s):  
Mingzhou Liu ◽  
Xin Xu ◽  
Jing Hu ◽  
Qiannan Jiang
Keyword(s):  
Gibbs Energy ◽  
Energy Function ◽  
Gaussian Mixture Models ◽  
Texture Features ◽  
Gaussian Mixture ◽  
Gibbs Energy Function ◽  
Road Detection ◽  
The Road ◽  
Detection Algorithms ◽  
Random Sample Consensus

Road detection algorithms with high robustness as well as timeliness are the basis for developing intelligent assisted driving systems. To improve the robustness as well as the timeliness of unstructured road detection, a new algorithm is proposed in this paper. First, for the first frame in the video, the homography matrix H is estimated based on the improved random sample consensus (RANSAC) algorithm for different regions in the image, and the features of H are automatically extracted using convolutional neural network (CNN), which in turn enables road detection. Secondly, in order to improve the rate of subsequent similar frame detection, the color as well as texture features of the road are extracted from the detection results of the first frame, and the corresponding Gaussian mixture models (GMMs) are constructed based on Orchard-Bouman, and then the Gibbs energy function is used to achieve road detection in subsequent frames. Finally, the above algorithm is verified in a real unstructured road scene, and the experimental results show that the algorithm is 98.4% accurate and can process 58 frames per second with 1024×960 pixels.

A WT-Based Edge Detection with Adaptive Threshold

2011 ◽  
Vol 204-210 ◽  
pp. 1386-1389
Author(s):  
Deng Yin Zhang ◽  
Li Xiao ◽  
Shun Rong Bo
Keyword(s):  
Wavelet Transform ◽  
Edge Detection ◽  
Threshold Value ◽  
Detection Algorithm ◽  
Adaptive Threshold ◽  
Value Iteration ◽  
Edge Detection Algorithm ◽  
Detection Algorithms ◽  
Image Edge ◽  
Threshold Setting

The existing edge detection algorithms with wavelet transform need to artificially set the threshold value and are lack of flexibility.To salve the limitations, in this paper, we propose a WT(wavelet transform)-based edge detection algorithm with adaptive threshold, which uses threshold value iteration method to achieve adaptive threshold setting. Comparison of experiment results for the CT image shows that the method which improve the clarity and continuity of the image edge can effectively distinguish edge and noise, and get more completely information of the edge. It has good application value in the fields of medical clinical diagnosis and image processing.

Cellular Automata Algorithms for Digital Image Processing

Biometrics ◽  
2017 ◽  
pp. 382-402
Author(s):  
Petre Anghelescu
Keyword(s):  
Image Processing ◽  
Cellular Automata ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Image ◽  
Image Understanding ◽  
Software Application ◽  
Detection Algorithms ◽  
Human Image ◽  
The Impact

In this paper are presented solutions to develop algorithms for digital image processing focusing particularly on edge detection. Edge detection is one of the most important phases used in computer vision and image processing applications and also in human image understanding. In this chapter, implementation of classical edge detection algorithms it is presented and also implementation of algorithms based on the theory of Cellular Automata (CA). This work is totally related to the idea of understanding the impact of the inherently local information processing of CA on their ability to perform a managed computation at the global level. If a suitable encoding of a digital image is used, in some cases, it is possible to achieve better results in comparison with the solutions obtained by means of conventional approaches. The software application which is able to process images in order to detect edges using both conventional algorithms and CA based ones is written in C# programming language and experimental results are presented for images with different sizes and backgrounds.

On-the-Road Detection of Driving While Intoxicated

1979 ◽  
Vol 23 (1) ◽  
pp. 263-266
Author(s):  
Douglas H. Harris
Keyword(s):  
Law Enforcement ◽  
Police Officers ◽  
Visual Cues ◽  
Frequency Of Occurrence ◽  
Road Detection ◽  
Patrol Officers ◽  
Law Enforcement Agencies ◽  
Driving While Intoxicated ◽  
The Road ◽  
On The Road

Visual cues were identified and procedures were developed to enhance on-the-road detection of driving while intoxicated (DWI) by police patrol officers. Related research was reviewed; police officers with demonstrated effectiveness in DWI detection were interviewed; DWI arrest reports were analyzed; and a study was conducted to determine the frequency of occurrence and relative discriminability of potential visual cues. Based on the results, a DWI detection Guide was developed; the Guide is currently being verified and evaluated in a field-study involving a sample of 10 law enforcement agencies.

scholarly journals An Application Study on Road Surface Monitoring Using DTW Based Image Processing and Ultrasonic Sensors

2020 ◽  
Vol 10 (13) ◽  
pp. 4490 ◽  
Author(s):  
Sunil Kumar Sharma ◽  
Haidang Phan ◽  
Jaesun Lee
Keyword(s):  
Image Processing ◽  
Cost Effective ◽  
Processing Technique ◽  
Road Surface ◽  
Image Processing Technique ◽  
Ultrasonic Sensors ◽  
The Road ◽  
Surface Irregularities ◽  
Road Surface Monitoring ◽  
Surface Monitoring

Road surface monitoring is an essential problem in providing smooth road infrastructure to commuters. This paper proposed an efficient road surface monitoring using an ultrasonic sensor and image processing technique. A novel cost-effective system, which includes ultrasonic sensors sensing with GPS for the detection of the road surface conditions, was designed and proposed. Dynamic time warping (DTW) technique was incorporated with ultrasonic sensors to improve the classification and accuracy of road surface detecting conditions. A new algorithm, HANUMAN, was proposed for automatic recognition and calculation of pothole and speed bumps. Manual inspection was performed and comparison was undertaken to validate the results. The proposed system showed better efficiency than the previous systems with a 95.50% detection rate for various road surface irregularities. The novel framework will not only identify the road irregularities, but also help in decreasing the number of accidents by alerting drivers.

scholarly journals Algorithm to Image Identification and Artix-7 FPGA Implementation for Adequate Edge Detection.

2020 ◽  
Vol 8 (5) ◽  
pp. 1656-1660
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Detection Algorithm ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
Low Contrast ◽  
Image Identification ◽  
Canny Edge ◽  
Set Up ◽  
Canny Edge Detection Algorithm

For any image identification based applications, edge detection is the primary step. The intention of the edge detection in image processing is to minimize the information that is not required in the analysis of identification of an image. In the process of reduction of insignificant data in the image, it may lead to some loss in information which in turn raise some problems like missing of boundaries with low contrast, false edge detection and some other noise affected problems. In order to reduce the effects due to noise, a modified version of popular edge detection algorithm “Canny edge detection algorithm” is proposed. Artix 7 FPGA board set up is used to implement, by using Xilinx platform the image that is obtained as output is displayed on monitor which is connected with FPGA board using connector port DVI. MATLAB Simulink is used for algorithm simulation and then it is executed on FPGA board using Xilinx platform. The results provide good motivation to use in different edge detection applications.

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