Image Resizing: Problem Solved!
All of us face the problem of bad image cropping or resizing frequently, where either the picture details get blurred or its proportions get messed up (elongation or squeezing)! Now, if this image needs to be used for an important situation, say in a legal document, it becomes extremely important to preserve its salient content and geometric consistency.
Researchers at IIT Gandhinagar have proposed a method* which prevents deformation of the critical features of an image on different screens, an essential problem for 3D visualization, now-a-days. The comparison of this procedure with existing state-of-the-art image retargeting techniques depicts that it can preserve the crucial details of a picture more efficiently. Meaning, we would get a blur-free and proportionate image!
Dr. Shanmuganathan Raman is a researcher and professor in Electrical Engineering at the Indian Institute of Technology, Gandhinagar. He, along with his PhD student Diptiben Patel, has developed a content-aware (related to artificial intelligence) image retargeting technique that protects the important contextual information of an image and performs much better as compared to the methods which are used by the world in the present times.
“We wanted to resize the image content according to different display sizes, ranging from as small as an iPhone screen to as big as that of a TV above 100 inches. It is a multimedia (computational) problem — it’s about how do you adapt a multimedia content to different target display devices, with a variety of aspect ratios and screen resolutions, as well as printers. We wanted to re-scale the picture properly, but we did not want to compromise on its clear visibility,” said Prof. Raman.
In simple terms, this mechanism is based on preserving only the essential information and throwing away details that are not important. The unimportant content is, generally, not perceptible to the human eye, and discarding it would lead to an effective rescaling of the image.
Seam carving was the first discrete method based on content-aware image retargeting. It can be understood as something which generates horizontal or vertical curves (seams). To resize a picture, it tracks down a curve with minimum energy level (least important information) and removes it. For this, there is a need to train the algorithm (a step-by-step procedure developed to solve a logical problem) involved in this process, about the difference between essential and unimportant details.
“Our study aimed to develop improved algorithms which can differentiate between the essential and non-essential part of the image content more effectively. We also tried to remove multiple insignificant curves at the same time, something known as accelerated seam carving, as compared to the conventional system of deleting one seam at a time. Moreover, this research is the first of its kind to focus on safeguarding reflection scene symmetry and scene text,” he continued.
In the case of different objects being present in the same image, this method resizes those objects simultaneously while successfully preserving the intrinsic geometry between them — the different depth levels of these objects with respect to one another remain protected, promoting better 3D visualization.
Explaining further, Prof. Raman said, “For example, the Taj Mahal at Agra is an intrinsic symmetry building. The existing methods of image retargeting destroy its picture symmetry in some way or the other (compressing or unnecessary cropping) while adjusting it to fit different display sizes. But, our method tries to preserve the Taj as much as possible, which is an example of its efficient object-awareness. Another example is that of the presence of texts in an image. The traditional techniques, often, fail to protect the text and lead to collapsed and squeezed words that are not clearly visible. Our method overcomes this limitation, showing effective text-awareness quality.”
As of now, this approach has only been tested on images. It needs to be tested on videos to have an understanding of its real-time efficacy. In order to make the entire process completely seamless, there is a need for a more robust algorithm that runs in real-time. It needs to be accelerated enough so as to minimize the time required for completing the entire procedure. For this, some of the operations need to be parallelized and solutions regarding the same need to found out. All this would, eventually, pave the way for the commercial utilization of this method.
“You don’t take a photograph, you make it.” Ansel Easton Adams, renowned landscape photographer and environmentalist of the 20th century
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- The results of this research have been published in -
a) “Object occlusion guided stereo image retargeting”, Pattern Recognition Letters, DOI: 10.1016/j.patrec.2019.07.018, Jul. 2019.
b) “Reflection symmetry aware image retargeting”, Pattern Recognition Letters, DOI: 10.1016/j.patrec.2019.04.013, Jul. 2019.
The video of this story (made by Devarsh Bharbhaya) can be accessed here.
