Extended Biologically Inspired Model for Object Recognition Based on Oriented Gaussian-Hermite Moment
Lu Yanfeng(吕彦锋); Kang Taekoo; Zhang Huazhen; Choi Inhwan; Lim Myotaeg
Source PublicationNeurocomputing
2014
Issue193Pages:155-166
AbstractHierarchical Model and X (HMAX) presents a biologically inspired model for robust object recognition. The HMAX model, based on the mechanisms of the visual cortex, can be described as a four-layer structure. Although the performance of HMAX in object recognition is robust, it has been shown to be sensitive to rotation, which limits the model's performance. To alleviate this limitation, we propose an Oriented Gaussian-Hermite Moment-based HMAX (OGHM-HMAX). In contrast to HMAX which uses a Gabor filter for local feature representation, OGHM-HMAX employs the Oriented Gaussian-Hermite Moment (OGHM), which is a local representation method that represents features and is robust against distortions. OGHM is an extension of the modified discrete Gaussian-Hermite moment (MDGHM). To show the effectiveness of the proposed method, experimental studies on object categorization are conducted on the CalTech101, CalTech5, Scene13 and GRAZ01 databases. Experimental results demonstrate that the performance of OGHM-HMAX is a significant improvement on that of the conventional HMAX.
KeywordObject Recognition Classification Hmax Oriented Gaussian-hermite Moment Gabor Features
Indexed BySCI
Language英语
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/15331
Collection复杂系统管理与控制国家重点实验室_机器人理论与应用
Recommended Citation
GB/T 7714
Lu Yanfeng,Kang Taekoo,Zhang Huazhen,et al. Extended Biologically Inspired Model for Object Recognition Based on Oriented Gaussian-Hermite Moment[J]. Neurocomputing,2014(193):155-166.
APA Lu Yanfeng,Kang Taekoo,Zhang Huazhen,Choi Inhwan,&Lim Myotaeg.(2014).Extended Biologically Inspired Model for Object Recognition Based on Oriented Gaussian-Hermite Moment.Neurocomputing(193),155-166.
MLA Lu Yanfeng,et al."Extended Biologically Inspired Model for Object Recognition Based on Oriented Gaussian-Hermite Moment".Neurocomputing .193(2014):155-166.
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