Edge Detection
119 papers with code • 8 benchmarks • 9 datasets
Edge Detection is a fundamental image processing technique which involves computing an image gradient to quantify the magnitude and direction of edges in an image. Image gradients are used in various downstream tasks in computer vision such as line detection, feature detection, and image classification.
Source: Artistic Enhancement and Style Transfer of Image Edges using Directional Pseudo-coloring
( Image credit: Kornia )
Benchmarks
These leaderboards are used to track progress in Edge Detection
Libraries
Use these libraries to find Edge Detection models and implementationsLatest papers with no code
Color Recognition in Challenging Lighting Environments: CNN Approach
Light plays a vital role in vision either human or machine vision, the perceived color is always based on the lighting conditions of the surroundings.
Applications of Tao General Difference in Discrete Domain
Tao general difference (TGD) is a novel theory and approach to difference computation for discrete sequences and arrays in multidimensional space.
Real-Time Asphalt Pavement Layer Thickness Prediction Using Ground-Penetrating Radar Based on a Modified Extended Common Mid-Point (XCMP) Approach
This study investigates the affecting factors and develops a modified XCMP method to allow automatic thickness prediction of in-service asphalt pavement with non-uniform dielectric properties through depth.
Systematic review of image segmentation using complex networks
This review presents various image segmentation methods using complex networks.
SuperEdge: Towards a Generalization Model for Self-Supervised Edge Detection
Edge detection is a fundamental technique in various computer vision tasks.
A fast numerical algorithm for finding all real solutions to a system of N nonlinear equations in a finite domain
A highly recurrent traditional bottleneck in applied mathematics, for which the most popular codes (Mathematica and Matlab) do not offer a solution, is to find all the real solutions of a system of N nonlinear equations in a certain finite domain of the N-dimensional space of variables.
Cable Slack Detection for Arresting Gear Application using Machine Vision
A situational awareness camera is utilized to collect video data of the cable interface region, machine vision algorithms are applied to reduce noise, remove background clutter, focus on regions of interest, and detect changes in the image representative of slack formations.
Depth Insight -- Contribution of Different Features to Indoor Single-image Depth Estimation
To this end, in this work, we quantify the relative contributions of the known cues of depth in a monocular depth estimation setting using an indoor scene data set.
Vision-Based Incoming Traffic Estimator Using Deep Neural Network on General Purpose Embedded Hardware
General-purpose electronic hardware has been used for in-situ image processing based on the edge-detection method.
FaultSeg Swin-UNETR: Transformer-Based Self-Supervised Pretraining Model for Fault Recognition
This paper introduces an approach to enhance seismic fault recognition through self-supervised pretraining.