An Adaptive and Robust Edge Detection Method Based on Edge Proportion Statistics


One of the most important preprocessing steps for high-level tasks in the field of image analysis and computer vision is edge detection. Because each image is unique, it is impossible to give a universal threshold that works for all photographs. This study proposes a real-time edge detector that is adaptive, robust, and effective. The images can be divided into three categories using 2D entropy and assigned a reference % based on edge proportion data for each category. Anchor points were more likely to be edge pixels than attached points in the gradient direction. Each of these points was then connected to another edge segment, each of which was a clean, contiguous, 1-pixel wide chain of pixels. The proposed edge detector outperforms traditional edge following methods in terms of detection accuracy, according to the findings of the experiments. It's also possible to use the real-time detection findings as input information for applications such as post-processing.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : A Natural Language Process-Based Framework for Automatic Association Word Extraction ABSTRACT: In psychology, word association has been extensively explored for exposing mental representations and relationships
PROJECT TITLE : Parkinson’s Disease Identification using KNN and ANN Algorithms based on Voice Disorder ABSTRACT: Because of its vast use, speech signal processing has received a lot of attention in recent years. We lead a comparative
PROJECT TITLE : An efficient Android malware detection system based on method-level behavioral semantic analysis ABSTRACT: Every day, 12 000 new Android malware samples will be developed, according to a recent report. The efficient
PROJECT TITLE : Modeling of effective path-length based on rain cell statistics for total attenuation prediction in satellite link ABSTRACT: The ITU-R suggests a worldwide rain-attenuation prediction model for satellite links,
PROJECT TITLE : A Multi-Domain and Multi-Modal Representation Disentangler for Cross-Domain Image Manipulation and Classification ABSTRACT: Deep learning and computer vision have been focusing on the development of interpretable

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry