Google is the No. 1 Image Recognition Engine: Report
Mon, November 29, 2021

Google is the No. 1 Image Recognition Engine: Report

With image recognition, it is easier for tech companies who monitor conversations to skim the amount of data and eliminate spam. / Photo by: alphaspirit via Shutterstock


About 80 percent of the content of the internet is visual. There are around 657 billion photos posted digitally each year that are shared through apps, websites, and social networks. One can start figuring out why image tagging holds its place as king of the content table. Image recognition has made it possible to identify visuals online with minimal fuss. 

With image recognition, it is easier for tech companies who monitor conversations to skim the amount of data, identify the most important interactions, eliminate spam, and help marketers focus on the most significant information. Analyzing visuals is extremely important in this day and age as offensive content, trolls, and massive doses of spam can create trouble on social media. To prevent this, image recognition monitors the photos or images associated with these messages. 

Artificial intelligence makes all the features of image recognition possible. With AI, the recognition system will learn to map out a relationship or pattern in the subsequent images supplied to it as a part of the learning process. It has also been gaining popularity in several industries. For instance, the eCommerce industry is using image recognition to present a more interactive view of the products to customers. A great example of this is CamFind API, which identifies objects like watches, shoes, bags, and sunglasses and returns purchasing options to the user.

The automotive industry is also being transformed by image recognition. Cars of the future are expected to detect obstacles and warn drivers about proximity to guardrails and walkways. Image recognition, with the help of deep learning, can read signs and stoplights and inform users about traffic. 

The Global Image Recognition Market

A recent report from Markets and Markets, a company that offers market research reports and custom research services on 30,000 high-growth opportunities, projected that the global image recognition market will grow to $38.9 billion by 2023 from only $15.9 billion in 2018. This accounts for a compound annual growth rate (CAGR) of 19.5 percent during the forecast period. According to Business Wire, the global leader in press release distribution and regulatory disclosure, hardware displays a potential growth of more than 19.8 percent, poised to reach $42.7 billion by 2025. 

The report showed that the US will maintain a 21.6 percent growth momentum during the forecast period. Germany will contribute over $2.1 billion to Europe’s image recognition market. The rest of Europe's markets will have a projected demand of more than $2.7 billion. China, the world’s second-largest economy and the new game-changer in global markets, shows a potential growth of 19.7 percent for the next few years. 

Some of the major drivers that will lead the growth of the global image recognition market include the increasing demand for security applications and products enabled with image recognition functions, increasing use of image recognition applications, and technology acceptance by various companies in different industries such as healthcare, automotive, and retail. These firms are significantly adopting image recognition technology in their businesses.

Google is Leading the Image Recognition Market

Various tech companies are working to provide extraordinary services to make clients rely on them more. Today, they are focused on providing more efficient results on image search. A recent report from Perficient Digital, the leading digital transformation consulting firm, analyzed the accuracy of Microsoft Azure, IBM Watson, Google Vision, and AWS Rekognition (Amazon).

According to Digital Information World, a platform of trending visual content for tech enthusiasts and entrepreneurs, the report aimed to make it easy for users to know about the efficiency of each search engine when it comes to image recognition. The researchers collected around 2,000 visuals from November 30, 2018 to January 8, 2019 and placed them into categories such as people, landscapes, charts, and products. After that, the team ran all these images through the image recognition search engines of Amazon, IBM, Google, and Microsoft and analyzed the search results.

The report showed that Google Vision is the best search engine with 81.7 percent accuracy. It is followed by AWS Rekognition (77.7 percent), Microsoft Azure (75.8 percent), and IBM Watson (55.6 percent). ClickZ, one of the largest digital marketing communities in the world today, reported that the accuracy of all search engines is at greater than 90 percent confidence. Google Vision and Microsoft Azure boasted impressively high confidence rates of 92.4 percent and 90.9 percent, respectively. For correlation, when the human group returned tags of over 90 percent certainty, 87.7 percent were accurate. 

Also, the report revealed that the scores for “human tagged” is fundamentally equal to the outcomes of the four search engines with a confidence score of 80 percent. Without a doubt, the precision of these engines is making amazing progress. The research looked at how human-like the image recognition engines were when it came to tagging images, which showed that their scores are considerably lower than the human tags. However, Google still excelled in all the search engines, matching 217 times.

“Humans can still see and explain what they are seeing to other humans better than machine APIs can. This is because of several factors, including language specificity and a greater contextual knowledge base,” the study concluded.

Overall, the study showed that Google’s advanced technologies and efficient response to commands are its key drivers for being number one in image search. It also provides unique content and a user-friendly interface as well as efficient results when it comes to image recognition. 


Google’s advanced technologies and efficient response to commands are its key drivers for being number one in image search. / Photo by: Tero Vesalainen via Shutterstock