<![CDATA[Image resizing is a process of processing images or images with the aim of changing the size of the image. The most commonly used methods are cropping or scaling. Scaling is changing the size of the image based on the scale. Contents in the image are not considered in scaling. Seam carving often uses energy functionality that is useful as a determinant of the pixel level contained in an image. Seam is a connecting path of image pixels both vertically and horizontally that is passed by a low energy function. Changing the image size using seam carving is considered better than cropping and scaling. However, the seam carving method still cannot protect the object that is considered the most important. In overcoming this weakness, we can use a combination of seam carving algorithm with salient detection. In this research, we will improve the two methods which function as thumbnail maker. The results of the salient detection of the most important areas of the image will be detected and as a reference in resizing the image (seam carving) The dataset uses 200 images. The accuracy value is calculated by distributing questionnaires to 100 respondents and producing an acceptance rate of 78% so that the results are Very Natural/Natural.]]>
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