Extracting Information and Size Prediction of Objects in Underwater Images using Image Processing Technique

G. Lakshmi, E. Salomon, Samruddhi Tendulkar
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Abstract

Underwater image analysis is the current research field since a lot of resources is available in ocean. The prediction about captured underwater images is not an easy task. So, far the prediction about underwater buried images have been done with the help of human being. To overcome this, in this paper, the prediction about buried/Sunken underwater object have been done using image processing technique with the concept of search and recovery method. The underwater images are considered as inputs and by using grab cut algorithm, the segmentation have been done. The Segmented image is compared with original object. So, it concluded by predicting the size of the object by using ratio between original object and segmented object. The same methodology is applied for predicting the size of the sub objects in the considered input image, and it works out.
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基于图像处理技术的水下图像中目标信息提取与大小预测
由于海洋资源丰富,水下图像分析是当前的研究领域。对捕获的水下图像进行预测并不是一件容易的事。迄今为止,水下埋藏图像的预测都是借助人类的力量完成的。为了克服这一问题,本文采用图像处理技术,结合搜索恢复法的概念,对被埋/沉没的水下目标进行了预测。以水下图像为输入,采用抓取切割算法对图像进行分割。将分割后的图像与原始目标进行比较。因此,利用原始目标与分割目标的比值来预测目标的大小。同样的方法被应用于预测所考虑的输入图像中子对象的大小,并且成功了。
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