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Frequency Component Extraction from Color Images for Specific Sound Transformation and Analysis

机译:从彩色图像提取特定声音变换和分析的频率分量提取

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This paper presents a method allowing the conversion of images into sound. Initially, a frequency component extraction is realized from the original image. At this stage, the image is divided into windows in order to represent consecutive different time periods using STFT. Then, the dominant frequencies of each window are mapped into corresponding sound frequencies through Fourier analysis. This procedure is applied twice and two series of sound frequency components are produced: The first is originated from the brightness of the image, the second from the dominant RGB layer. The connection between the visual impression of the image and the psychoacoustic effect of the sound mapping is done by using different musical scales according to the dominant color of the image. The results revealed that the melody extracted from this analysis produces a certain psychoacoustic impression, as it has reported by several volunteers. Despite the fact that volunteers could not always do the association between image and sound, they could hardly believe that the music was produced by an algorithmic procedure.
机译:本文介绍了一种方法,允许将图像转换为声音。最初,从原始图像实现频率分量提取。在此阶段,将图像分成窗口,以便使用STFT表示连续的不同时间段。然后,通过傅立叶分析将每个窗口的主导频率映射到相应的声音频率。该过程应用了两次,产生了两种系列的声频分量:首先是从图像的亮度,第二个来自主导RGB层的亮度。通过根据图像的显着颜色使用不同的音乐尺度来完成图像的视觉印象和声音映射的心理声学效果之间的连接。结果表明,从该分析中提取的旋律产生了一定的心理声学印象,因为它已被几个志愿者报告。尽管志愿者不能总是在图像和声音之间进行关联,但他们很难相信音乐是由算法过程产生的。

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