Frequency component extraction from color images for specific sound transformation and analysis

Gizem Akti, Dionysis Goularas
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引用次数: 7

Abstract

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.
从彩色图像中提取频率分量,用于特定声音的变换和分析
本文提出了一种将图像转换为声音的方法。首先,从原始图像中提取频率成分。在这个阶段,图像被分割成窗口,以便使用STFT表示连续的不同时间段。然后,通过傅里叶分析将每个窗口的主导频率映射为相应的声音频率。这个过程被应用两次,产生了两个系列的声音频率分量:第一个来自图像的亮度,第二个来自主导RGB层。图像的视觉印象与声音映射的心理声学效果之间的联系是根据图像的主色使用不同的音阶来完成的。结果显示,从这种分析中提取的旋律产生了某种心理声学印象,正如几名志愿者所报告的那样。尽管志愿者并不总是能将图像和声音联系起来,但他们很难相信音乐是由算法程序产生的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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