arXiv subjects

ZhenZhou Wang

Publications and source records attributed to ZhenZhou Wang.

4 recordsLinked to original sources

arXiv2025

A Comparative Tutorial of the Histogram-based Image Segmentation Methods

The histogram of an image is the accurate graphical representation of the numerical grayscale distribution and it is also an estimate of the probability distribution of image pixels. Therefore, histogram has been widely adopted to calculate the clustering means and partitioning thresholds for image segmentation. There have been many classical histogram-based image segmentation methods proposed and played important roles in both academics and industry. In this tutorial, the histories and recent advances of the histogram-based image segmentation techniques are first reviewed and then they are divided into four categories: (1) the means-based method, (2) the Gaussian-mixture-model-based method, (3) the entropy-based method and (4) the feature-points-based method. The purpose of this tutorial is threefold: 1) to teach the principles of the classical histogram-based image segmentation methods to the interested readers; 2) to evaluate the advantages and disadvantages of these classical histogram-based image segmentation methods objectively; 3) to compare the performances of these classical histogram-based image segmentation methods with state-of-the-art deep learning based methods objectively.

eess.IV↗

arXiv2024

The active visual sensing methods for robotic welding: review, tutorial and prospect

The visual sensing system is one of the most important parts of the welding robots to realize intelligent and autonomous welding. The active visual sensing methods have been widely adopted in robotic welding because of their higher accuracies compared to the passive visual sensing methods. In this paper, we give a comprehensive review of the active visual sensing methods for robotic welding. According to their uses, we divide the state-of-the-art active visual sensing methods into four categories: seam tracking, weld bead defect detection, 3D weld pool geometry measurement and welding path planning. Firstly, we review the principles of these active visual sensing methods. Then, we give a tutorial of the 3D calibration methods for the active visual sensing systems used in intelligent welding robots to fill the gaps in the related fields. At last, we compare the reviewed active visual sensing methods and give the prospects based on their advantages and disadvantages.

cs.RO↗

arXiv2023

Segmentation of the Left Ventricle by SDD double threshold selection and CHT

Automatic and robust segmentation of the left ventricle (LV) in magnetic resonance images (MRI) has remained challenging for many decades. With the great success of deep learning in object detection and classification, the research focus of LV segmentation has changed to convolutional neural network (CNN) in recent years. However, LV segmentation is a pixel-level classification problem and its categories are intractable compared to object detection and classification. In this paper, we proposed a robust LV segmentation method based on slope difference distribution (SDD) double threshold selection and circular Hough transform (CHT). The proposed method achieved 96.51% DICE score on the test set of automated cardiac diagnosis challenge (ACDC) which is higher than the best accuracy reported in recently published literatures.

eess.IV↗

arXiv2019

Bottleneck detection by slope difference distribution: a robust approach for separating overlapped cells

To separate the overlapped cells, a bottleneck detection approach is proposed in this paper. The cell image is segmented by slope difference distribution (SDD) threshold selection. For each segmented binary clump, its one-dimensional boundary is computed as the distance distribution between its centroid and each point on the two-dimensional boundary. The bottleneck points of the one-dimensional boundary is detected by SDD and then transformed back into two-dimensional bottleneck points. Two largest concave parts of the binary clump are used to select the valid bottleneck points. Two bottleneck points from different concave parts with the minimum Euclidean distance is connected to separate the binary clump with minimum-cut. The binary clumps are separated iteratively until the number of computed concave parts is smaller than two. We use four types of open-accessible cell datasets to verify the effectiveness of the proposed approach and experimental results showed that the proposed approach is significantly more robust than state of the art methods.

cs.CV↗