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Hough Transform and OCR Assignment Help | Sample Assignment

Updated: Nov 24, 2023




Are you currently grappling with the formidable challenge of addressing a complex computer vision project, such as To implement the Ηough transform algorithm and detect circles/ellipses, and To make a simple Optical Character Recognition (OCR) system for numeric digits using the generalized Ηough transform. Are you in search of expert guidance to navigate through the intricacies of implementing the Hough transform algorithm and developing a robust Optical Character Recognition (OCR) system? Whether you're a student aiming to enhance your computer vision skills or a professional looking to delve into advanced techniques, CodersArts is here to offer the support you need.


What We Offer

At CodersArts, we understand the complexities involved in implementing computer vision methods, especially when dealing with tasks like the Hough transform and OCR. In this project, we explore the world of computer vision, focusing on detecting circles/ellipses using the Hough transform and building an OCR system for numeric digits. We provide comprehensive solutions to critical questions, such as localizing elliptical outlines in color images and recognizing numbers in black and white images.


Get Assignment Solution


If you find yourself in need of a solution for this assignment or have similar tasks at hand, don't hesitate to reach out to us. We specialize in delivering thorough solutions tailored to the specific challenges presented in the assignment. Whether it's the Hough transform, OCR, or other computer vision tasks, we've got you covered.


Sample Assignment


Overview

The goal of this assignment is twofold:

  1. To implement the Ηough transform algorithm and detect circles/ellipses, revisiting the board game scenario from Assignment 1 while extending the family of computer vision methods you can use to tackle it.

  2. To make a simple Optical Character Recognition (OCR) system for numeric digits using the generalized Ηough transform.

Optionally, perform generalized Ηough transform on the slanted cards of the dataset given, and record your findings in terms of the effect of the shearing, scaling and translation of the cards.


We provide you with two datasets:

  1. Colored images of circular cards with 8 symbols. The images are taken using a professional grade camera/lens and are high-resolution so they need some form of preprocessing. The images vary in their translation, however there are multiple “consecutive” images with cards that are gradually rotated in front of the camera.

  2. Black and white images with rendered numbers on them. Each image has a corresponding text file with the ground truth (i.e. the actual number depicted on the image).

Part A: Hough transform


For the first task/program of the assignment you will need to write a program that implements the Hough transform so that, given a color image (see for example the above sample image) you can robustly detect the elliptical outline of the circular card.


Peculiarities of the given images in the dataset are that they are high resolution so this gives you more pixels to work with, however it also requires some preprocessing steps. As we discussed in the class, the complexity of a vision system depends heavily on the assumptions we make explicitly or implicitly. In the case of our “board game”, we consider a scenario, according to which:

  • The background is out of focus

  • A hand manipulating the card can intersect with its border

  • Seeing the cards from different angles “skews” their shape

  • The cards have different translations. Your task is to implement the Hough transform and, using it, highlight the contour of the cards.


Part B: Generalized Hough transform


For the second task/program you are given black and white images that depict a number.


Each data_xxxxx.jpg file contains a unique number and is paired with a solution_xxxxx.txt file that contains the correct solution. By implementing a generalized Hough transform you are asked to write a program that given each one of the 100 images provided, will be able to correctly recognize the depicted numbers. Doing so, entails that you first build models of each of the 10 digits and then you try to localize them in each given image.


As soon as you detect the presence of digits, you may exploit the fact that, in our problem formulation, all numbers are written horizontally. This can help you place your digit detections in the proper order.


Images have the following characteristics:

  • The background is either completely black or white.

  • The text is either white or black depending on the background.

  • The number is positioned randomly in the image.

  • The scale, rotation and font of the text is the same across all images

  • The image has been gaussian blurred\


Generalized Hough (optional, extra credit)


Optionally (for extra credit) and given that you have a generalized Hough transform implementation from part B, you can use it to detect the shapes on cards. For example, in the image below, you might use the generalized Hough to detect the presence of a particular, selected object. Specifically, you need to (a) build gradient-based generalized Hough transform representations of a certain/selected object and (b) run your code to try to localize it in an image.


You can also study and report how rotating the card in 3D affects the output of your method.


What to turn in

You should turn in both your code and a report discussing your solution and results. The report should contain the following:

  • Method/system description: A brief description of your implemented solution. What implementation choices did you make, and how did they affect the quality of the result and/or the speed of computation? What are some artifacts and/or limitations of your implementation, and what are possible reasons for them? Ideally, the description should be such that a skillful programmer should be able to reproduce fairly accurately your system based on your description, alone.

  • Qualitative results: The input color image(s) that you tried and the output values that your system returned.

  • Other information (if applicable): Brief description of ideas that you attempted, but did not work.


Grading policy

Grading depends on:

(a) the assessment of the quality of the proposed solution.

(b) the quality of the written report.



Deliverables You Can Expect

When you opt for CodersArts for assistance with this assignment, you can anticipate a comprehensive package. We furnish all the essential information and resources required for you to excel in this project. Additionally, we offer a detailed breakdown of the code workflow, ensuring a thorough understanding of the implementation.


How We Can Help You Overcome Challenges


CodersArts offers tailored solutions to conquer the complexities of this project:

  • Expert Cloud Computing Guidance: Our seasoned experts in cloud computing provide comprehensive guidance for tackling intricate tasks using Spark frameworks and best design patterns.

  • Efficient Data Processing: Learn techniques to efficiently acquire, store, and preprocess extensive datasets, optimizing your data computation tasks for better performance.

  • Error Handling: Receive timely assistance in debugging and resolving issues that might arise during the development and execution of your computer vision solution.

  • Tailored Support: We provide one-on-one support, tailored to your specific project needs, ensuring that you have the resources and guidance necessary to succeed.


Why Choose CodersArts Expertise


Our team consists computer vision experts with a wealth of industry experience. We customize our support to your proficiency level and the unique demands of your project, ensuring a perfect fit for your requirements. Timely support is our commitment, recognizing the importance of meeting deadlines. Our dedication goes beyond completing your assignment; we ensure you thoroughly comprehend the core concepts of computer vision and image processing. Our competitive pricing makes expert guidance in computer vision within reach for all.


If you're in search of a solution for this assignment or require assistance with similar projects, feel free to reach out to us via email at contact@codersarts.com. We are dedicated to providing you with the best solutions tailored to your specific needs. Your success is our priority, and we look forward to being your trusted partner in conquering complex computer vision assignments and projects. Contact us today and experience the difference CodersArts can make in your academic and professional journey.


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