• Monday, July 04, 2022

Uncategorized

Image Reverse Search

By: Admin Super

Reverse image search is nowadays one of the essential tools to know the source of the images you use. There are plenty of tools offered by a lot of giant companies who do an image search and provide a mechanism for others to use it. We know there is the yahoo reverse image search. This reverse image engine is sturdy and performs so fast and efficiently that you won’t even notice the time it took to show the results. So, let us look into further how yahoo reverse search engine works.

Working

Working with a reverse image search engine like “reverseimagesearch.org” is relatively simple as it doesn’t take any input of much data and gives output quickly. You don’t need to know all the keywords for your image to find or a particular keyword for your image. Yahoo image search also provides searching of sample images that you might want to know the source of. There are various algorithms used to perform a search like this. We all know how big is the database for images on the internet; it’s not easy to find pictures rather than to reverse find it. 

Algorithms used 

It turns out leisurely for the Yahoo search by image, which uses all these different algorithms to find an accurate source. The first algorithm which is used here is  

  • Scale-invariant feature transform – This algorithm is used to detect the local feature of the image, like little attributes we can find to describe an image. This algorithm is robust and powers yahoo reverse image search tool to a greater extent.

 

  • Maximally stable extremal regions – Maximally stable extremal regions or (MSER) are widely used in image reverse search tools. This algorithm provides a lot of flexibility is in order to differentiate between the two images. MSER detects different image features, and by this data, it differentiates between the two images. So, even if two images are similar but not identical, it can show the difference. 

 

  • Vocabulary Tree – Vocabulary Tree is also termed as the bag-of-words model, which is used to classify images by treating them as words. The BOW model works on three factors – 
    • Feature Detection – detects the features of the image at every image point.
    • Feature Description – After the detection, it then makes a description out of it.
    • Codebook Generation – after the description of the images are done, a codebook is generated of the image, which is further used to find the source of the image.

Uses

  1.   The best use is to locate the source of any image we want to use the yahoo reverse search engine.
  2.   With this search engine, we not only find the image that we wish to but also, we can find the best versions of it like if we have a low-resolution image, we can find a higher resolution image.
  3.   By searching, we can see the source and the webpage where it is uploaded initially.
  4.   If we want to know about who created the image, we can know about the content creator, and if we want more pictures of that kind, we can ask.
  5.   With the image, we want to do a reverse search, and we can know a lot more about it.

 

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