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IntelligentPhoto : A design for photo enhancement and human identification by histogram equalization, enhancing filters and Haar-Cascades

机译:IntelligentPhoto:通过直方图均衡,增强滤镜和Haar级联来进行照片增强和人识别的设计

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Flickr and Instagram are known to be an online crowdsourced photo sharing applications which people can share experiences with others. SmartPhoto is such a framework that was developed for this purpose. In the example of post-disaster recovery first responders survey the damage by taking pictures and then transfer them back to the rescue center. A problem with this system is how to abolish the redundancy and to find the most indicative photos containing human. SmartPhoto measure the utility of the crowdsourced photos based on the metadata of the photos which is accessible geometrical and geographical information. But this system did not address the problem with low quality images. If we enhance the low quality photos the perception factor of the photos get increased. The proposed system called IntelligentPhoto addresses this problem by first measuring the quality of the photos by checking the amount of blurriness and noisiness. It is based on by applying Laplacian kernel to the photos. The system then uses techniques known as Histogram Equalization to enhance the dark photos and perform other enhancing operations like noise reduction, smoothing, de-blurring, and edge enhancement to the low quality photos using wiener filter, median filter and smoothing filter. Selection algorithm are applied to find the most indicative photos and to abolish the redundancy in photos. Feature Feature matching is done to the selected photos by applying Haarcascades. Panoramas of the photos are constructed and it is send to rescue center for further action. This system is applicable to post-disaster recovery.
机译:Flickr和Instagram是一种在线众包照片共享应用程序,人们可以与他人共享经验。 SmartPhoto是为此目的而开发的框架。在灾难后恢复的示例中,第一响应者通过拍照来调查损害,然后将其转移回救援中心。该系统的问题是如何消除冗余并找到最具指示性的包含人的照片。 SmartPhoto根据照片的元数据(可访问的几何和地理信息)来衡量众包照片的效用。但是该系统不能解决低质量图像的问题。如果我们增强低质量的照片,则照片的感知因素会增加。所提出的名为IntelligentPhoto的系统通过首先检查模糊和噪点的数量来测量照片的质量来解决此问题。它基于对照片应用拉普拉斯内核的基础。然后,系统使用称为“直方图均衡化”的技术来增强暗照片,并使用维纳滤镜,中值滤镜和平滑滤镜对低质量照片执行其他增强操作,如降噪,平滑,去模糊和边缘增强。应用选择算法来查找最具指示性的照片,并消除照片中的冗余。功能通过应用Haarcascades对选定的照片进行功能匹配。照片的全景图被构建,并将其发送到救援中心以采取进一步行动。该系统适用于灾难后恢复。

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