Visual saliency detection and image segmentation technology and applications in image processing implemented in Java

With the rapid development of digital information technology and computer science, image processing technology has been widely used in various fields. Among them, visual saliency detection and image segmentation technology are currently one of the most popular image processing technologies and are widely used in fields such as medicine, transportation, security, and video surveillance.

As a powerful programming language, Java has good cross-platform and object-oriented characteristics, and has also been widely used in the fields of image processing and computer vision. In this article, we will introduce visual saliency detection and image segmentation technology in image processing implemented in Java and its applications.

1. Visual saliency detection technology

Visual saliency detection is used in image processing to simulate the human visual system’s perception and detection of salient targets in images. A method of positioning the process. Its purpose is to distinguish areas of interest and targets from a large amount of image data and improve the efficiency and effect of image processing and analysis.

The visual saliency detection technology implemented in Java mainly includes GMM method, optical flow method and deep learning method. Among them, the GMM method is a visual saliency detection method based on Gaussian mixture model. This method uses multiple Gaussian distributions to describe the pixel distribution of the image, and detects the difference between the pixel distribution of the salient target in the image and the background pixel distribution. differences to achieve significance detection.

The optical flow method is a method to achieve saliency detection based on the motion information of pixels in the image. This method determines the location and shape of salient targets by calculating the distance and direction of movement between pixels in the image. The deep learning method is a new visual saliency detection method developed in recent years. It realizes target detection and recognition based on the deep neural network model, and can effectively solve the saliency detection problem in complex scenes.

2. Image segmentation technology

Image segmentation refers to the process of dividing the pixels in the image into several regions based on similarity or other rules. Its purpose is to separate the target of interest in the image from the background and other areas to facilitate further analysis and processing of the target.

Image segmentation technology implemented in Java mainly includes segmentation methods based on clustering, segmentation methods based on image edges and textures, and segmentation methods based on deep learning.

The clustering-based segmentation method is the simplest and most direct image segmentation method. It achieves segmentation by dividing image pixels into multiple categories according to similarity and dividing pixels in the same category into a region. . Segmentation methods based on image edges and textures divide image areas based on edge and texture information in the image, and usually use edge detection and texture descriptor technologies for processing.

In recent years, with the development of deep learning technology, segmentation methods based on deep learning have gradually become a popular research field. This method uses a convolutional neural network model to achieve segmentation and recognition of targets in images, and can effectively handle segmentation problems in complex scenes.

3. Application Case

Visual saliency detection and image segmentation technology have been widely used in various fields. The following are several application cases:

Medicine: Visual saliency detection and image segmentation technology can be applied to medical image processing, such as analyzing diseased areas and healthy areas in medical imaging data such as MRI and CT. .

Traffic: In the field of transportation, visual saliency detection and image segmentation technology can be used in vehicle recognition, pedestrian detection, lane line recognition, etc., thereby improving traffic safety.

Security: In the security system, through visual saliency detection and image segmentation processing of video surveillance images, the detection and identification of abnormal behaviors and dangerous items can be achieved.

Summary

This article introduces the visual saliency detection and image segmentation technology in image processing implemented in Java. These technologies can be widely used in many fields. Through the analysis and processing of image data, they improve the efficiency and accuracy of image processing, and also promote the development of digital information technology and computer science.

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