Efficient Handwritten Digit Recognition based on Histogram of Oriented Gradients and SVM

Ebrahimzadeh, Reza; Jampour, Mahdi

doi:10.5120/18229-9167

Cited by 59 publications

(37 citation statements)

References 8 publications

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“…Fish initialization: for each fish of the school, the position x ij was initialized according to (2). …”

Section: B Binary Fish School Searchmentioning

confidence: 99%

“…This occurs due to the particular writing style of each individual. Even though there are only ten characters to be recognized (0 to 9), the digits are universal symbols, its stroke can be considered as a base for the other characters and its interpretation can be a solution applied into several domains [1] [2]. Besides, HDR is an active topic within the pattern recognition area since several works have already presented different approaches in order to solve this problem [3].…”

Section: Introductionmentioning

confidence: 99%

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Metaheuristics for feature selection in handwritten digit recognition

Seijas

Carneiro

Santana

et al. 2015

2015 Latin America Congress on Computational Intelligence (LA-CCI)

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Recognition of handwritten digits by computers is a common research topic in the pattern recognition area and has application in several domains. Many techniques can be applied in order to maximize the recognition performance, such as image preprocessing, feature extraction, feature selection and classification stages. This paper focuses on the assessment of three swarm intelligence optimization algorithms for feature selection optimization, called Binary Fish School Search (BFSS), Advanced Binary Ant Colony Optimization (ABACO) and Binary Particle Swarm Optimization (BPSO), for the recognition of handwritten digits. These meta-heuristics were applied to the well-known handwritten digit database MNIST, preprocessed with the CDF 9/7 Wavelet Transform. We used support vector machine (SVM) for the classification task. A considerable reduction in the number of features used for digit classification on the MNIST database with a small loss in the classification rates was observed.Keywords-feature selection; binary optimization; support vector machine; wavelet transform; handwritten digit recognition; binary fish school search; advanced binary ant colony optimization; binary particle swarm optimization.

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“…Fish initialization: for each fish of the school, the position x ij was initialized according to (2). …”

Section: B Binary Fish School Searchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Metaheuristics for feature selection in handwritten digit recognition

Seijas

Carneiro

Santana

et al. 2015

2015 Latin America Congress on Computational Intelligence (LA-CCI)

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show abstract

“…One interesting application used HOG features to detect landmines in ground-penetrating radar [40]. The HOG was also used for facial expression recognition [39] and other object recognition, such as plant leaves [37], handwritten digits [38], and off-line signatures [36]. The BRISK descriptor is generated from a configurable circular sampling pattern.…”

Section: Research Backgroundmentioning

confidence: 99%

Artwork Identification for 360-Degree Panoramic Images Using Polyhedron-Based Rectilinear Projection and Keypoint Shapes

Jin

Kim

2017

Applied Sciences

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Abstract:With the increased development of 360-degree production technologies, artwork has recently been photographed without authorization. To prevent this infringement, we propose an artwork identification methodology for 360-degree images. We transform the 360-degree image into a three-dimensional sphere and wrap it with a polyhedron. On the sphere, several points are located on the polyhedron to determine the width, height, and direction of the rectilinear projection. The 360-degree image is divided and transformed into several rectilinear projected images to reduce the adverse effects from the distorted panoramic image. We also propose a method for improving the identification precision of artwork located at a highly distorted position using the difference of keypoint shapes. After applying the proposed methods, identification precision is increased by 45% for artwork that is displayed on a 79-inch monitor in a seriously distorted position with features that were generated by scale-invariant feature transformations.

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“…Proposed by Navneet Dalal and Bill Triggs in [10], HOG was originally designed for human detection. Later, HOG demonstrates its effectiveness in many computer vision tasks, such as texture classification [46], digit classification [19] and face analysis related tasks [14,52]. Based on C x and C y , magnitudes of the gradients are defined by |G| = C 2 x + C 2 y , and orientations of gradients are calculated with θ = arctan Cy Cx .…”

Section: Histogram Of Oriented Gradientsmentioning

confidence: 99%

Head pose estimation and its application in TV viewers' behavior analysis

Wu¹,

Liang²,

Ho³

2016

2016 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)

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As a reliable indicator of visual gaze direction, head pose implies a person's visual attention and interest. Therefore, head pose information extracted from face images serves as important input in many applications. In this thesis, a coarse-to-fine head pose estimation method is proposed, by decomposing the original pose space in a hierarchical structure.The estimation begins with a coarse step to identify a subspace that encompasses a set of head pose candidates. Then a subsequent fine estimation is conducted within the subspace, generating a refined result. Besides, to eliminate irrelevant information within a face image, we propose to detect Region of Interest (ROI) by exploring importance degree of image points. Furthermore, we build an application of analyzing TV viewers' behaviors from video recordings, by integrating face detection, face tracking and head pose estimation. Based on head pose and face motion, a viewer's behavior is identified to be focused or unfocused.

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Efficient Handwritten Digit Recognition based on Histogram of Oriented Gradients and SVM

Cited by 59 publications

References 8 publications

Metaheuristics for feature selection in handwritten digit recognition

Metaheuristics for feature selection in handwritten digit recognition

Artwork Identification for 360-Degree Panoramic Images Using Polyhedron-Based Rectilinear Projection and Keypoint Shapes

Head pose estimation and its application in TV viewers' behavior analysis

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