Proceedings ArticleDOI
A Novel Automated Solver for Sudoku Images
Kshitij Gupta,Sagar Khatri,Muneeb Hasan Khan +2 more
- pp 1-6
Reads0
Chats0
TLDR
This paper attempts to explore the solving of Sudoku puzzles (as commonly found in newspapers and mobile games) using image processing, machine learning algorithms for OCR, and an efficient solving algorithm to compute the correct answer.Abstract:
This paper attempts to explore the solving of Sudoku puzzles (as commonly found in newspapers and mobile games) using image processing, machine learning algorithms for OCR, and an efficient solving algorithm to compute the correct answer. We use various image processing techniques, such as Image Thresholding, Erosion and Dilation, etc. to convert a high-resolution and colored camera-generated image of the physical Sudoku puzzle into a format that can be digitally operated upon, in order to isolate the contents of the 9 × 9 puzzle grid correctly. We then use our custom Optical Character Reader (OCR), which is based on the k-NN machine learning algorithm, in order to correctly identify the digits contained in the grid and place them in the respective positions in a digital copy of the Sudoku grid, which is then processed by an efficient Sudoku solving algorithm, to compute the correct solution.read more
References
More filters
Journal ArticleDOI
Algorithms for the reduction of the number of points required to represent a digitized line or its caricature
TL;DR: In this paper, two algorithms to reduce the number of points required to represent the line and, if desired, produce caricatures are presented and compared with the most promising methods so far suggested.
An Improved k-Nearest Neighbor Classification Using Genetic Algorithm
N. Suguna,K. Thanushkodi +1 more
TL;DR: In this article, an improved version of KNN is proposed in which GA is combined with KNN to improve its classification performance, instead of considering all the training samples and taking k-neighbors, the GA is employed to take k-NEighbors straightaway and then calculate the distance to classify the test samples.
Mathematics of Sudoku I
TL;DR: In this article, the number of essentially different Sudoku grids can be found by allowing various possible symmetries, such as reflecting a grid to get another valid grid, and relabeling all the entries to give another grid.
Book ChapterDOI
Adaptive k-nearest-neighbor classification using a dynamic number of nearest neighbors
Stefanos Ougiaroglou,Alexandros Nanopoulos,Apostolos N. Papadopoulos,Yannis Manolopoulos,Tatjana Welzer-Druzovec +4 more
TL;DR: It is demonstrated that the execution of the nearest neighbor search algorithm can be interrupted if some criteria are satisfied, and a decision can be made without the computation of all k nearest neighbors of a new object.