Nave Weinberg & Shlomi Nissim

Slides:



Advertisements
Similar presentations
Patient information extraction in digitized X-ray imagery Hsien-Huang P. Wu Department of Electrical Engineering, National Yunlin University of Science.
Advertisements

Review from this Lesson
Spreadsheet Vocabulary Split the screen so you can see the words AND the crossword puzzle AND the quiz at the same time.
The Web Wizards Guide to HTML Chapter Six Tables.
OpenCV Introduction Hang Xiao Oct 26, History  1999 Jan : lanched by Intel, real time machine vision library for UI, optimized code for intel 
QR Code Recognition Based On Image Processing
Maayan Zehavi. Pic-a-pix is a paint by number logic puzzle, in which cells in a grid must be colored or left blank according to numbers at the side of.
Histogram Analysis to Choose the Number of Clusters for K Means By: Matthew Fawcett Dept. of Computer Science and Engineering University of South Carolina.
Fingerprint Imaging: Wavelet-Based Compression and Matched Filtering Grant Chen, Tod Modisette and Paul Rodriguez ELEC 301 : Rice University, Houston,
Image Segmentation Region growing & Contour following Hyeun-gu Choi Advisor: Dr. Harvey Rhody Center for Imaging Science.
Instructor: Mircea Nicolescu Lecture 13 CS 485 / 685 Computer Vision.
COMP322/S2000/L181 Pre-processing: Smooth a Binary Image After binarization of a grey level image, the resulting binary image may have zero’s (white) and.
Segmentation Divide the image into segments. Each segment:
Fitting a Model to Data Reading: 15.1,
Kakuro Puzzles game Chang-Yin Lin CS491B December
Robust estimation Problem: we want to determine the displacement (u,v) between pairs of images. We are given 100 points with a correlation score computed.
Lecture 6: Feature matching and alignment CS4670: Computer Vision Noah Snavely.
3x3x3 Rubik’s Cube Solver Kevin Van Kammen Kyle Rupnow Jason Lavrenz.
SUDOKU PUZZLE EXTRACTION PROJECT BY: BORIS SPEKTOR.
Sum Things Missing ! Let’s Play Sum Things Missing ! Rules: The Clue (dark box) is the Sum of the Digits (white boxes) Only use Digits 1 thru 9 (no 0)
SOLVING THE KAKURO PUZZLE Andreea Erciulescu Department of Mathematics, Colorado State University, Fort Collins (Mentor: A. Hulpke)
Solving Sudoku Mark PTTLS Micro teach. Solving Sudoku What is a Sudoku? A Sudoku is a number puzzle based on a 9x9 grid made up from smaller 3x3 blocks.
Computer Vision Spring ,-685 Instructor: S. Narasimhan Wean Hall 5409 T-R 10:30am – 11:50am.
WP3 - 3D reprojection Goal: reproject 2D ball positions from both cameras into 3D space Inputs: – 2D ball positions estimated by WP2 – 2D table positions.
UNIT 3 TEMPLATE AND EXCEPTION HANDLING. Introduction  Program errors are also referred to as program bugs.  A C program may have one or more of four.
By: Adam Hebert.  Why Sudoku?  Attempts at an App  MATLAB Implementation - Use of webcam - Algorithm  Problems with method  Demonstration  Questions.
M4.A.3 Compute accurately and fluently and make reasonable estimates. M4.A.3.2 Compute using fractions or decimals (written vertically or horizontally.
COMMON APPLICATION FUNCTIONS Presentation. Bullets  Symbols used to organize data into a list.  This  Is  An  Example  Of  A  Bullet  List.
Topic 10 - Image Analysis DIGITAL IMAGE PROCESSING Course 3624 Department of Physics and Astronomy Professor Bob Warwick.
Lecture 4: Feature matching CS4670 / 5670: Computer Vision Noah Snavely.
©Robomatter – Distribution or copying without permission is prohibited. 3B STEM Computer Science 1 ©Robomatter – Distribution or copying without permission.
**NEW Unit Plan** TOPIC: Microsoft Word Word Processing: Software that uses text and formatting features to create documents. Microsoft Word: Software.
Methods for Multiplying. Standard Algorithm Partial Products Draw table with dimensions of digits in each number. Ex.
It’s All About Properties of Equality. How could properties of equality be applied to solve this equation? Example 1: 3x + 11 = 32 What is the value of.
Lesson 4 - Revising the Document Layout Microsoft Word 2010.
Lecture 16 Maximum Matching. Incremental Method Transform from a feasible solution to another feasible solution to increase (or decrease) the value of.
DR. NAVEED AHMAD DEPARTMENT OF COMPUTER SCIENCE UNIVERSITY OF PESHAWAR LECTURE-5 Advance Algorithm Analysis.
Digital Image Processing Chapter 9: Morphological Image Processing 5 September 2007 Digital Image Processing Chapter 9: Morphological Image Processing.
Programming for Beginners Martin Nelson Elizabeth FitzGerald Lecture 5: Software Design & Testing; Revision Session.
Horizontal scans were taken every millimeter between the center of the swarm and the end of multiple tendrils using the z-stack function of a Nikon Eclipse.
Image Segmentation & Template Matching Multimedia Signal Processing lecture on Petri Hirvonen.
Reading the Graduated Cylinder And All about the Meniscus.
Checkers Cheaters. Goals Detection of the board and the pieces (blacks and whites). Display of an optimal move using animated arrows according to a non-trivial.
Sudoku Solver Comparison A comparative analysis of algorithms for solving Sudoku.
Eurecom, 6 Feb 2007http://biobimo.eurecom.fr Project BioBiMo 1.
Eye regions localization Balázs Harangi – University of Debrecen Ciprian Pop – Technical University of Cluj-Napoca László Kovács – University of Debrecen.
Thai OCR using Template Matching Algorithm By Manoch Pracha Assignment 1.
The Percent Proportion. To solve a proportion, multiply the numbers that are diagonal, divide by the one that’s left.
By: David Gelbendorf, Hila Ben-Moshe Supervisor : Alon Zvirin
Dividing Polynomials The objective is to be able to divide a polynomial by a monomial.
Headlines - Font: Ariel, Size:32, white Breadtext: Font: Ariel, Size: 22, color white This is a table cell with color RGB 96,96,96 Headline Running text.
~ ~ ~ ~ CLUES ~ ~ ~ ~ Left\: 15= __ x __ 70= __ x __ x __ 165= __ x __ x __ 38= __ x __ Down:
Computer Technology – January Read the definition, think of the answer, then click to see if you are right. An application program which helps you.
Multiplying Decimals 12/7/2015. To Multiply: You do not align the decimals. Instead, place the number with more digits on top. Multiply Count the number.
Image Text & Audio hacks. Introduction Image Processing is one of the fastest growing technology in the field of computer science. It is a method to convert.
Grouping and Segmentation. Sometimes edge detectors find the boundary pretty well.
IMAGE PROCESSING Tadas Rimavičius.
Edge Detection slides taken and adapted from public websites:
Chapter 10 Image Segmentation
In Search of the Optimal Set of Indicators when Classifying Histopathological Images Catalin Stoean University of Craiova, Romania
Depth estimation and Plane detection
Introduction to Computational and Biological Vision Keren shemesh
Image Primitives and Correspondence
Feature description and matching
M4.A.3 Compute accurately and fluently and make reasonable estimates.
Follow-up question Factorize x2 + 2x – 15. Solution
Binary Image processing بهمن 92
Image Processing, Lecture #10
Filtration Filtration methods for binary images
Building pattern  Complete the following tables and write the rule 
Presentation transcript:

Nave Weinberg & Shlomi Nissim

Goals Detect a “Hidato” puzzle from a “Yediot Ahronot” newspaper. Display a digital view of the “Hidato” on an Android smart-phone. Solve the “Hidato” and display the full solution or clues to the user.

Stage 1: Hidato Detection Using adaptive threshold and morphological erosion for detecting clear contours. Finding the biggest contour in the center of the image.

Stage 2: Aligning Finding the “Hidato” four edges by dividing the max contour to four areas, computing min/max value for each local area . Applying Projective Transformation from those edges to fixed points.

Stage 3: Numbers Detection After aligning, the cells location in the table are known. Applying normalized cross correlation with 61 number templates on each cell in order to detect the correct number, while ignoring white (empty) cells.

Stage 4: Solving the “Hidato” Using a backtracking algorithm. Guess a solution by trying one of several choices. If the guess proves incorrect, the computation backtracks to the last point of guess and guesses a different choice.

Limitations The "Hidauto" table should be in the center of the image. The picture orientation must be from bottom to top.

GUI Example run: https://youtu.be/VaOgrYyjT4A