Classification of Daytime and Night Based on Intensity and Chromaticity in RGB Color Image

Kihong Park, Y. Lee
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引用次数: 2

Abstract

Classification of daytime and night in the color image is a very important task in image processing based on color images acquired from CCTV. Also, weather classification must be performed before performing image processing such as weather report, shadow removal and fog detection. In this paper, we proposed the classification, whether a color image is daytime or night. We first set the range of pixels in the gray level image from 0 to 50, from 51 and over 101, and we estimated each range as daytime, evening and night. In the first step, it is estimated based on the intensity and chromaticity of the image. If the classification result based on the intensity and chromaticity image is the same, the process is terminated. Otherwise, the k-means segmentation is used in the second step to determine the final classification. Some experiments are conducted so as to verify the proposed method, and the classification is well performed. The execution time results up to the first step are about 0.31 seconds on average, and the execution up to the second step is changed according to the resolution of the image.
基于RGB彩色图像强度和色度的白天和黑夜分类
基于CCTV采集的彩色图像,彩色图像的昼夜分类是图像处理中的一项重要任务。此外,天气分类必须在进行天气报告、阴影去除和雾检测等图像处理之前进行。在本文中,我们提出了分类,无论是白天或夜间的彩色图像。我们首先设置灰度图像中的像素范围,从0到50,从51到超过101,我们估计每个范围为白天,晚上和晚上。在第一步,它是基于图像的强度和色度估计。如果基于强度和色度图像的分类结果相同,则终止该过程。否则,在第二步中使用k-means分割来确定最终的分类。通过实验验证了该方法的有效性,分类效果良好。执行到第一步的时间结果平均约为0.31秒,执行到第二步的时间根据图像的分辨率变化。
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