Directional Connected Components Algorithm Based on Gradient Information

Abstract

This paper presents a directional connected components algorithm that overcomes the problem of overlapping components by gradient information. The proposed algorithm replaces the binary matrix with the directional matrix that contains the gradient information. The directional matrix contains both the gradient magnitude and angle and provides the merge decisions of neighboring pixels for solving the problem of overlapping edges. The proposed algorithm improves the performance of the connected components algorithm in the classification of features and candidates using edge information. Experimental results demonstrate that the proposed algorithm can resolve the problem of overlapping components, and prevent false connections between components and background under various circumstances.

Connected pixels-based image smoothing filter

“…In conclusion, pixel connectivity is a fundamental concept in image processing and computer vision that refers to the relationships between neighboring pixels in a digital image. It plays a crucial role in many image analysis tasks, and it is quantified using connectivity matrices or graphs [13][14][15][16]. The definition of pixel connectivity can be extended to 3D images, and it is closely related to other concepts in image processing such as image topology and morphological operations.…”