Context-Aware Handwritten and Optical Character Recognition Using a Combination of Wavelet Transform, PCA and Neural Networks

Phan, Ngoc Hoang; Bui, Thi Thu Trang

doi:10.1007/978-3-319-29236-6_25

Cited by 2 publications

(3 citation statements)

References 8 publications

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“…Besides the experimental results of algorithms [4,[16][17][18][19][20] showed that using combination of wavelet transform, PCA and neural networks gave more effective performance of object recognition. In these algorithms, neural networks were used to recognize objects based on their features, which extracted by using the combination of wavelet transform and PCA.…”

Section: Eai Endorsed Transactions On Context-aware Systems and Applimentioning

confidence: 99%

“…Besides we can also quickly calculate the wavelet transform. So wavelet transform becomes one of the most effective methods, which are used to extract image features to classify (recognize) objects [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20].…”

Section: Extracting Hand Pose Features Using Wavelet Transformsmentioning

confidence: 99%

“…In the algorithms [4,[11][12][13][14][15][16][17][18][19][20] wavelet transform is effectively used to solve the task of pattern recognition on…”

Section: Introductionmentioning

confidence: 99%

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Context-aware hand poses classifying on images and video-sequences using a combination of wavelet transforms, PCA and neural networks

Phan¹,

Trang²

2017

EAI Endorsed Transactions on Context-aware Systems and Applicat

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In this paper we propose novel context-aware algorithms for hand poses classifying on images and video-sequences. The proposed hand poses classifying on images algorithm based on Viola-Jones method, wavelet transform, PCA and neural networks. On the first step, the Viola-Jones method is used to find the location of hand pose on images. Then, on the second step, the features of hand pose are extracted using combination of wavelet transform and PCA. Finally, on the last step, these extracted features are classified by multi-layer feed-forward neural networks. The proposed hand poses classifying on video-sequences algorithm based on the combination of CAMShift algorithm and proposed hand poses classifying on images algorithm. The experimental results show that the proposed algorithms effectively classify the hand pose in difference light contrast conditions and compete with state-of-the-art algorithms.

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Section: Eai Endorsed Transactions On Context-aware Systems and Applimentioning

confidence: 99%

Section: Extracting Hand Pose Features Using Wavelet Transformsmentioning

confidence: 99%

See 1 more Smart Citation

Context-aware hand poses classifying on images and video-sequences using a combination of wavelet transforms, PCA and neural networks

Phan¹,

Trang²

2017

EAI Endorsed Transactions on Context-aware Systems and Applicat

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Context-Aware Hand Pose Classifying Algorithm Based on Combination of Viola-Jones Method, Wavelet Transform, PCA and Neural Networks

Phan

Bui

2017

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Context-Aware Handwritten and Optical Character Recognition Using a Combination of Wavelet Transform, PCA and Neural Networks

Cited by 2 publications

References 8 publications

Context-aware hand poses classifying on images and video-sequences using a combination of wavelet transforms, PCA and neural networks

Context-aware hand poses classifying on images and video-sequences using a combination of wavelet transforms, PCA and neural networks

Context-Aware Hand Pose Classifying Algorithm Based on Combination of Viola-Jones Method, Wavelet Transform, PCA and Neural Networks

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