基于彩色图像分割的数字技术图像识别方案研究（英文）

Research on digital technology image recognition scheme based on color image segmentation

数字图像处理技术对于艺术领域的影响越来越大,特别是图像分割技术。针对美术图像识别中的分割精度问题,提出了一种基于canny算子边缘检测和GrabCut算法的美术图像自动分割方案。首先,通过RGB模型对图像进行预处理,实现对图像进行平滑和锐化。然后,采用canny算子边缘检测对待分割图像进行平滑滤波并计算梯度值。最后,采用GrabCut算法在RGB颜色空间中进行最小化能量函数计算,并按照随机的方法将分割区域与其他区域进行合并从而构造出一张分割图。实验对比结果表明:在直接视觉和量化分析上,相比现有分割算法,提出的方案表现出更好的分割效果。

Digital image processing technology has an increasing influence on the art field, especially image segmentation technology. For segmentation accuracy problems in the art of image recognition, an art image automatic segmentation scheme based on edge detection of Canny operator and GrabCut algorithm is proposed in this paper. First, the image will be preprocessed by the RGB model to achieve smooth and sharp image. Then, the edge detection of the canny operator is used to smooth the filtered image and calculate the gradient value. Finally, the GrabCut algorithm is used to minimize the energy function calculation in the RGB color space, and the segmentation region is combined with other regions according to a random method to construct a segmentation map. The experimental comparison results show that compared with the existing segmentation algorithms, the proposed scheme shows better segmentation effect in direct visual and quantitative analysis.