I was first introduced to the idea of Matrices and determinants in my high school linear algebra class. Back then my only goal was to remember how to compute them using the given formulas. When I visited the determinants again after many years for one of my computer vision projects, It became clear I had […]
If you get on a plane that can carry 100 or more passengers at a time, there is a 99% chance that one of the passengers shares the same birthday as yours. If you get into a bus with a capacity of 50 passengers, you have a 97% chance of finding someone who shares your […]
Correlation is the measure of how two or more variables are related to one another, also referred to as linear dependence. An increase in demand for a product increases its price, also called the demand curve, traffic on roads at certain intervals of time of the day, the amount of rain correlates with grass fires, […]
Definition The Fréchet distance is usually explained using the analogy of a man walking his dog. A man is walking a dog on a leash: the man can move on one curve, the dog on the other; both may vary their speed, but backtracking is not allowed. What is the length of the shortest leash […]
When dealing with a large number of data, It’s a good practice to remove any outliers before further processing unless there is a good reason to keep them. Outliers in simple words are datapoint which are unusually far away from the rest of the dataset. For the lazy, here is the code to find outliers […]
In character recognition, the distance between two edges of a stroke, measured perpendicular to the stroke centerline is called the stroke width. Take a look at the below image. The length of lines marked in Red gives the stroke width of the character. There are quite a few ways to identify the stroke width, In […]
In this post I will be talking about how we can use Hough Transform to detect and correct Skewness of a document image. There have been many research papers published around this problem and it keeps getting published even today on various journals mainly because its still largely an unsolved problem. I had previously written […]
One of the important steps in OCR is the thresholding process. It helps us in separating the text regions (foreground) from the background. If you apply a thresholding algorithm like OTSU or Sauvola, you might end up with a lot of noise. Some of your text regions may even get categorized as background. Take a […]
This is for my reference and this might come in handy for others too. All Tesseract options CLI Examples Command Example Notes tesseract sample_images/image2.jpg stdout To print the output to standard output tesseract sample_images/image2.jpg sample_images/output By default the output will be named outbase.txt. tesseract sample_images/image2.jpg sample_images/output -l eng -l is for language. English is default […]
The problem of building systems that mimic human behavior is not an easy one to solve. Neural Nets solve those problems in one way but if someone thinks that it’s the right way doesn’t know enough about Artificial Intelligence. When you show a child a picture of a dog, just one picture, the child can […]