Image segmentation techniques have been widely applied in many fields such as pattern
recognition and feature extraction. For the primate visual attention model, the perceptual …

Otsu's criteria is a popular image segmentation approach that selects a threshold to
maximise the inter-class variance of the distribution of intensity levels in the image. The …

为了实现图像的有效分割, 提出了一种自适应多阈值图像分割方法, 能够自动获得最佳分割阈值
数目和阈值. 该方法对灰度直方图进行合适尺度的连续小波变换, 将小波变换曲线中幅值为负的 …

Image segmentation is a fundamental step for many image analysis and preprocessing
tasks. In segmentation, minimum cross entropy (MCE) based multilevel thresholding is …

针对阈值分割存在精确性不高和分割效率低的问题, 提出一种基于模糊集理论的迭代多值化图像
分割方法. 采用自顶向下的迭代分割策略综合考虑分割区域的灰度分布特征和各像素点的邻域 …

Finding the infected regions in medical image modalities is a crucial and challenging task. In
this paper, a new image segmentation method is introduced to detect the COVID-19 …

Object detection is a really crucial application of image processing. It is of essential value for
object active surveillance and various other applications. Hence, the object detection has …

Segmentation is one of the most important tasks in image processing that endeavors to
classify pixels into two or more groups according to their intensity levels and a threshold …

Evolutionary algorithms (EAs) are designed to find the best solution by removing the
solutions with the lowest fitness. As a result, this research provides an evolutionary algorithm …

High level tasks in image analysis and understanding are based on accurate image
segmentation which can be accomplished through multilevel thresholding. In this paper, we …