Shape Representation Robust to the Sketching Order Using Distance Map and Direction Histogram
Kiwon Yun,Junyeong Yang,Hyeran Byun +2 more
- pp 421-430
TLDR
A powerful shape representation to recognize sketches drawn on a pen-based input device is proposed by using the combination of distance map and direction histogram, which represents rich information to recognize an input sketch.Abstract:
We propose a powerful shape representation to recognize sketches drawn on a pen-based input device. The proposed method is robust to the sketching order by using the combination of distance map and direction histogram. A distance map created after normalizing a freehand sketch represents a spatial feature of shape regardless of the writing order. Moreover, a distance map which acts a spatial feature is more robust to shape variation than chamfer distance. Direction histogram is also able to extract a directional feature unrelated to the drawing order by using the alignment of the spatial location between two neighboring points of the stroke. The combination of these two features represents rich information to recognize an input sketch. The experiment result demonstrates the superiority of the proposed method more than previous works. It shows 96% recognition performance for the experimental database, which consists of 28 freehand sketches and 10 on-line handwritten digits.read more
Citations
More filters
Journal ArticleDOI
Stroke Sequence-Dependent Deep Convolutional Neural Network for Online Handwritten Chinese Character Recognition
TL;DR: Wang et al. as mentioned in this paper proposed a stroke sequence-dependent deep convolutional neural network (SSDCNN), which uses stroke sequence information and eight-directional features of Chinese characters for online handwritten Chinese character recognition (OLHCCR).
Posted Content
Stroke Sequence-Dependent Deep Convolutional Neural Network for Online Handwritten Chinese Character Recognition
TL;DR: The proposed SSDCNN reduced the recognition error by approximately 18.0% as compared with that of the winning system in the ICDAR 2013 competition and reached a new state-of-the-art (SOTA) standard with an accuracy of 97.94%.
Patent
Hand-drawn sketch recognition
TL;DR: In this article, a model is formed from a plurality of images having visual features similar to the visual features of the sketch, and the model may include object topics representative of categories which may correspond to the subject of a sketch and shape topics representing of the visual feature of the original sketch.
References
More filters
Journal ArticleDOI
Shape matching and object recognition using shape contexts
TL;DR: This paper presents work on computing shape models that are computationally fast and invariant basic transformations like translation, scaling and rotation, and proposes shape detection using a feature called shape context, which is descriptive of the shape of the object.
Journal ArticleDOI
Online and off-line handwriting recognition: a comprehensive survey
TL;DR: The nature of handwritten language, how it is transduced into electronic data, and the basic concepts behind written language recognition algorithms are described.
Journal ArticleDOI
Hierarchical chamfer matching: a parametric edge matching algorithm
TL;DR: The hierarchical chamfer matching algorithm matches edges by minimizing a generalized distance between them in a hierarchical structure, i.e. in a resolution pyramid, which reduces the computational load significantly.
Proceedings Article
Parametric correspondence and chamfer matching: two new techniques for image matching
TL;DR: The matching of image and map features is performed rapidly by a new technique, called "chamfer matching", that compares the shapes of two collections of shape fragments, at a cost proportional to linear dimension, rather than area.
Proceedings ArticleDOI
Shape context and chamfer matching in cluttered scenes
TL;DR: It is shown that the robustness of shape matching can be increased by including a figural continuity constraint, and the combined shape and continuity cost is minimized using the Viterbi algorithm on features, resulting in improved localization and correspondence.
Related Papers (5)
Part-based deformable object detection with a single sketch
A curvature estimation for pen input segmentation in sketch-based modeling
Dae Hyun Kim,Myoung-Jun Kim +1 more