{"title":"从彩色图像中提取频率分量,用于特定声音的变换和分析","authors":"Gizem Akti, Dionysis Goularas","doi":"10.1109/IPTA.2012.6469573","DOIUrl":null,"url":null,"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.","PeriodicalId":267290,"journal":{"name":"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Frequency component extraction from color images for specific sound transformation and analysis\",\"authors\":\"Gizem Akti, Dionysis Goularas\",\"doi\":\"10.1109/IPTA.2012.6469573\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":267290,\"journal\":{\"name\":\"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)\",\"volume\":\"65 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPTA.2012.6469573\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPTA.2012.6469573","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Frequency component extraction from color images for specific sound transformation and analysis
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.