Answers.Body: <p>To perform image recognition you have to find a way to represent an image with certain features.</p>
  
  <p>One of the defining characteristics of a good image recognition algorithm are it's ability to detect salient regions, that is, regions which contain the most information</p>
  
  <p>There is a lot of attention on deep learning for content-based image classification at the moment. You can achieve decent results by implementing deep learning having three or more layers of CNN's where each layer is responsible for extracting one or more feature of the image.</p>
  
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-12-15T21:25:55.447Z
Answers.Text: Thanks. I'm not a CNN guy myself. But is there any pointer to a source code that given a logo image, it can detect if it exists or not?
Answers.UserDisplayName: Mary
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-12-16T06:42:31.883Z
Answers.Text: Hey, please check out DeepLogo on Github by Satoj Kovic. It is written on Python and uses CNN's to recognise brand logo's. I have posted the link below. Cheers. https://github.com/satojkovic/DeepLogo
Answers.UserDisplayName: Seth Simba
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-12-15T19:21:54.243Z
Answers.LastActivityDate: 2017-12-15T19:21:54.243Z
Answers.UserDisplayName: Seth Simba
Answers.Body: <p>Because it is video input and the logos are usually stationary because they are layered over the live or recorded frames by either hardware or software, the task is not difficult.  Logos also usually have limited color palettes and crisp edges.  The features of their fonts, when they spell words or acronyms are usually consistent too.  These are generalities that can be exploited in deep learning.</p>
  
  <p>As with the other similar question posted by this author, a combination of LSTM and CNN layers can be trained to find and isolate the logo.  With some image tricks, the image behind the logo can also be reconstructed with a reasonable accuracy and reliability from the pixels around the logo through a similar set of learning techniques.</p>
  
  <p>These are a few starting points for the development.</p>
  
  <ul>
  <li><a href="http://www.ivl.disco.unimib.it/activities/logo-recognition" rel="nofollow noreferrer">Deep Learning for Logo Recognition &mdash; Imaging and Vision Laboratory</a></li>
  <li><a href="https://medium.com/@akarshzingade/logo-detection-using-yolov2-8cda5a68740e" rel="nofollow noreferrer">Logo detection using YOLOv2 – Akarsh Zingade</a></li>
  <li><a href="https://github.com/satojkovic/DeepLogo" rel="nofollow noreferrer">GitHub &mdash; satojkovic/DeepLogo: A brand logo recognition system using deep convolutional neural networks</a></li>
  <li><a href="https://towardsdatascience.com/logo-detection-in-images-using-ssd-bcd3732e1776" rel="nofollow noreferrer">Logo detection in Images using SSD – Towards Data Science</a></li>
  <li><a href="https://arxiv.org/abs/1701.02620" rel="nofollow noreferrer">1701.02620 &mdash; Deep Learning for Logo Recognition</a></li>
  </ul>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-11-08T02:46:42.690Z
Answers.LastActivityDate: 2018-11-08T02:46:42.690Z
Answers.UserDisplayName: Douglas Daseeco
Body: <p>I am trying to detect a TV channel logo inside a video file. So, simply, given an input <code>.mp4</code> video, detect if it has that logo present in a specific frame, say the first frame, or not.</p>
  <p>Here's the first example of a frame with a logo.</p>
  <img src="https://i.sstatic.net/qa3Tp.png" width="400">
  <p>Here's the second example.</p>
  <img src="https://i.sstatic.net/LCDtS.png" width="400">
  <p>We have that logo in advance (although might not be %100 of the same size) and the location is always fixed.</p>
  <p>I already have a pattern matching-based approach. But that requires the pattern to be %100 the same size.</p>
  <p>I would like to use Deep Learning and Neural networks to achieve that. How can I do that? I believe CNNs can have a higher efficiency.</p>
  
Tags: <neural-networks><convolutional-neural-networks><pattern-recognition><algorithm-request><model-request>
Title: How can I use neural networks for detecting TV channel logos in video frames?
UserDisplayName: Mary
ThreadText: # How can I use neural networks for detecting TV channel logos in video frames?
  
  (Asked by: username_0 on 2017-12-15)
  
  I am trying to detect a TV channel logo inside a video file. So, simply, given an input `.mp4` video, detect if it has that logo present in a specific frame, say the first frame, or not.
  
  Here's the first example of a frame with a logo.
  
  ![](https://i.sstatic.net/qa3Tp.png)
  
  Here's the second example.
  
  ![](https://i.sstatic.net/LCDtS.png)
  
  We have that logo in advance (although might not be %100 of the same size) and the location is always fixed.
  
  I already have a pattern matching-based approach. But that requires the pattern to be %100 the same size.
  
  I would like to use Deep Learning and Neural networks to achieve that. How can I do that? I believe CNNs can have a higher efficiency.
  
  **Tags:** neural-networks, convolutional-neural-networks, pattern-recognition, algorithm-request, model-request
  
  ---
  
  ## 2 answers
  
  ### Answer by username_1 on 2017-12-15. Score: 5
  
  To perform image recognition you have to find a way to represent an image with certain features.
  
  One of the defining characteristics of a good image recognition algorithm are it's ability to detect salient regions, that is, regions which contain the most information
  
  There is a lot of attention on deep learning for content-based image classification at the moment. You can achieve decent results by implementing deep learning having three or more layers of CNN's where each layer is responsible for extracting one or more feature of the image.
  
  > **Comments:**
  > **username_0**: Thanks. I'm not a CNN guy myself. But is there any pointer to a source code that given a logo image, it can detect if it exists or not?  
  > **username_1**: Hey, please check out DeepLogo on Github by Satoj Kovic. It is written on Python and uses CNN's to recognise brand logo's. I have posted the link below. Cheers. https://github.com/satojkovic/DeepLogo  
  
  ---
  
  ### Answer by username_2 on 2018-11-08. Score: 3
  
  Because it is video input and the logos are usually stationary because they are layered over the live or recorded frames by either hardware or software, the task is not difficult. Logos also usually have limited color palettes and crisp edges. The features of their fonts, when they spell words or acronyms are usually consistent too. These are generalities that can be exploited in deep learning.
  
  As with the other similar question posted by this author, a combination of LSTM and CNN layers can be trained to find and isolate the logo. With some image tricks, the image behind the logo can also be reconstructed with a reasonable accuracy and reliability from the pixels around the logo through a similar set of learning techniques.
  
  These are a few starting points for the development.
  
  * [Deep Learning for Logo Recognition — Imaging and Vision Laboratory](http://www.ivl.disco.unimib.it/activities/logo-recognition)
  * [Logo detection using YOLOv2 – Akarsh Zingade](https://medium.com/@akarshzingade/logo-detection-using-yolov2-8cda5a68740e)
  * [GitHub — satojkovic/DeepLogo: A brand logo recognition system using deep convolutional neural networks](https://github.com/satojkovic/DeepLogo)
  * [Logo detection in Images using SSD – Towards Data Science](https://towardsdatascience.com/logo-detection-in-images-using-ssd-bcd3732e1776)
  * [1701.02620 — Deep Learning for Logo Recognition](https://arxiv.org/abs/1701.02620)
  
  
  ---
  
  