Palmprint recognition using Gabor-based local invariant features

Pan, Xin; Ruan, Qiuqi

doi:10.1016/j.neucom.2008.11.019

Cited by 57 publications

(39 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The number of samples is different in each experiment. The proposed hierarchical recognition method compares with those currently usually used recognition methods such as Gabor, [9] statistical method. [10] The experimental results show that the average correct recognition rates of these methods are 96.82%, 89.93%, 85.98% in simulation of 300 times, respectively.…”

Section: Experiments and Results Analysis (1) Establish A Standard Temmentioning

confidence: 99%

See 1 more Smart Citation

A hierarchical target recognition method based on image processing

Sun

Xiong³

et al. 2014

AIR

View full text Add to dashboard Cite

In order to provide an accurate and rapid target recognition method for some military affairs, public security, finance and other departments, this paper studied firstly a variety of fuzzy signal, analyzed the uncertainties classification and their influence, eliminated fuzziness processing, presents some methods and algorithms for fuzzy signal processing, and compared with other methods on image processing. Where, the fuzzy signal processing is that a blurred signal is dealt with by eliminating fuzziness. Moreover, this paper used the wavelet packet analysis to carry out feature extraction of target for the first time, extracted the coefficient feature and energy feature of wavelet transformation, gave the matching and recognition methods, compared with the existing target recognition methods by experiment, and presented the hierarchical recognition method. In target feature extraction process, the more detailed and rich texture feature of target can be obtained by wavelet packet to image decomposition to compare with the wavelet decomposition. In the process of matching and recognition, the hierarchical recognition method is presented to improve the recognition speed and accuracy. The wavelet packet transformation is used to carry out the image decomposition. Through experiment results, the proposed recognition method has the high precision, fast speed, and its correct recognition rate is improved by an average 6.13% than that of existing recognition methods. These researches development in this paper can provide an important theoretical reference and practical significance to improve the real-time and accuracy on fuzzy target recognition.

show abstract

Section: Experiments and Results Analysis (1) Establish A Standard Temmentioning

confidence: 99%

“…The proposed hierarchical recognition method and the usual used recognition methods [9,10] are compared from two aspects that are the computing speed and the correct recognition rate. Table 3 gives the results of a comprehensive comparison.…”

Section: Experiments and Results Analysis (1) Establish A Standard Temmentioning

confidence: 99%

A hierarchical target recognition method based on image processing

Sun

Xiong³

et al. 2014

AIR

View full text Add to dashboard Cite

show abstract

“…The literature [11] provided an updated survey of palmprint recognition methods, and presented a comparative study to evaluate the performance of the state-of-the-art palmprint recognition methods. According to [11], the proposed classification approach compares with those currently usually used approaches such as FCM [6], Median filter [9], Gabor [12] and Fourier transform [13]. The experimental results show that the average correct classification rates of these approaches are 95.57%, 94.11%, 93.24%, 92.45% and 88.17% in simulation of 500 times, respectively.…”

Section: Experiments and Analysismentioning

confidence: 98%

Target Image Classification through Encryption Algorithm Based on the Biological Features

Chen¹,

Wu²,

Yang³

2015

IJIS

View full text Add to dashboard Cite

In order to effectively make biological image classification and identification, this paper studies the biological owned characteristics, gives an encryption algorithm, and presents a biological classification algorithm based on the encryption process. Through studying the composition characteristics of palm, this paper uses the biological classification algorithm to carry out the classification or recognition of palm, improves the accuracy and efficiency of the existing biological classification and recognition approaches, and compares it with existing main approaches of palm classification by experiments. Experimental results show that this classification approach has the better classification effect, the faster computing speed and the higher classification rate which is improved averagely by 1.46% than those of the main classification approaches.

show abstract

“…Statistical approaches transform an input image into another domain and divide the transformed image into small regions. Then statistical features are extracted from each small region [13,14]. According to the results of these studies, line-based approaches are deemed to produce the most promising results.…”

Section: Introductionmentioning

confidence: 99%

Palmprint Verification Using Multi-scale Gradient Orientation Maps

Kim

2011

Journal of the Optical Society of Korea

View full text Add to dashboard Cite

This paper proposes a new approach to palmprint verification based on the gradient, in which a palm image is considered to be a three-dimensional terrain. Principal lines and wrinkles make deep and shallow valleys on a palm landscape. Then the steepest slope direction in each local area is first computed using the Kirsch operator, after which an orientation map is created that represents the dominant slope direction of each pixel. In this study, three orientation maps were made with different scales to represent local and global gradient information. Next, feature matching based on pixel-unit comparison was performed. The experimental results showed that the proposed method is superior to several state-of-the-art methods. In addition, the verification could be greatly improved by fusing orientation maps with different scales.

show abstract

Palmprint recognition using Gabor-based local invariant features

Cited by 57 publications

References 10 publications

A hierarchical target recognition method based on image processing

A hierarchical target recognition method based on image processing

Target Image Classification through Encryption Algorithm Based on the Biological Features

Palmprint Verification Using Multi-scale Gradient Orientation Maps

Contact Info

Product

Resources

About