2014/11/05 by Osvaldo Pereira, Esley Torre, Pereira, Osvaldo +5
Computer Science · #Advanced Image and Video Retrieval Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image Retrieval and Classification Techniques #Medical Image Segmentation Techniques #cs.CV
paper · pdf · doi:10.48550/arxiv.1411.1297
arxiv created 2014/11/05 · openalex publication_date 2014/11/05 · arxiv updated 2016/08/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Edges of an image are considered a crucial type of information. These can be extracted by applying edge detectors with different methodology. Edge detection is a vital step in computer vision tasks, because it is an essential issue for pattern recognition and visual interpretation. In this paper, we propose a new method for edge detection in images, based on the estimation by kernel of the probability density function. In our algorithm, pixels in the image with minimum value of density function are labeled as edges. The boundary between two homogeneous regions is defined in two domains: the spatial/lattice domain and the range/color domain. Extensive experimental evaluations proved that our edge detection method is significantly a competitive algorithm.