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Full-Text Articles in Physical Sciences and Mathematics
Industrial Computer Vision Using Undefined Feature Extraction, Phil Evans, John A. Fulcher, Philip Ogunbona
Industrial Computer Vision Using Undefined Feature Extraction, Phil Evans, John A. Fulcher, Philip Ogunbona
Professor Philip Ogunbona
This paper presents an application of computer The implementation and operation of the system is vision in a real-world uncontrolled environment found at BHP Steel Port Kembla. The task is visual identification of torpedo ladles at a Blast Furnace wlahdilceh. is achieved by reading numbers attached to each 3. IMPLEMENTATION Number recognition is achieved through use of feature extraction using a Multi-Layer Perceptron (MLP) Artificial Neural Network (ANN). The novelty in the method used in this application is that the features the MLP is being trained to extract are undefined before the MLP is initialised. The results of the MLP …
Real-Time Facial Feature Point Extraction, Ce Zhan, Wanqing Li, Philip Ogunbona, Farzad Safaei
Real-Time Facial Feature Point Extraction, Ce Zhan, Wanqing Li, Philip Ogunbona, Farzad Safaei
Professor Philip Ogunbona
Localization of facial feature points is an important step for many subsequent facial image analysis tasks. In this paper, we proposed a new coarse-to-fine method for extracting 20 facial feature points from image sequences. In particular, the Viola-Jones face detection method is extended to detect small-scale facial components with wide shape variations, and linear Kalman filters are used to smoothly track the feature points by handling detection errors and head rotations. The proposed method achieved higher than 90% detection rate when tested on the BioID face database and the FG-NET facial expression database. Moreover, our method shows robust performance against …
Wavelet-Based Feature-Adaptive Adaptive Resonance Theory Neural Network For Texture Identification, Jiazhao Wang, Golshah Naghdy, Philip Ogunbona
Wavelet-Based Feature-Adaptive Adaptive Resonance Theory Neural Network For Texture Identification, Jiazhao Wang, Golshah Naghdy, Philip Ogunbona
Professor Philip Ogunbona
A new method of texture classification comprising two processing stages, namely a low-level evolutionary feature extraction based on Gabor wavelets and a high-level neural network based pattern recognition, is proposed. The design of these stages is motivated by the processes involved in the human visual system: low-level receptors responsible for early vision processing and the high-level cognition. Gabor wavelets are used as extractors of ‘‘lowlevel’’ features that feed the feature-adaptive adaptive resonance theory (ART) neural network acting as a high-level ‘‘cognitive system.’’ The novelty of the model developed in this paper lies in the use of a self-organizing input layer …
New Feature-Based Image Adaptive Vector Quantisation Coder, Jamshid Shanbehzadeh, Philip O. Ogunbona
New Feature-Based Image Adaptive Vector Quantisation Coder, Jamshid Shanbehzadeh, Philip O. Ogunbona
Professor Philip Ogunbona
It is difficult to achieve a good low bit rate image compression performance with traditional block coding schemes such as transform coding and vector quantization, without regard for the human visual perception or signal dependency. These classical block coding schemes are based on minimizing the MSE at a certain rate. This procedure results in more bits being allocated to areas which may not be visually important and the resulting quantization noise manifests as a blocking artifact. Blocking artifacts are known to be psychologically more annoying than white noise when the human visual response is considered. While image adaptive vector quantization …
2d To Pseudo-3d Conversion Of "Head And Shoulder" Images Using Feature Based Parametric Disparity Maps, Chaminda Weerasinghe, Philip Ogunbona, Wanqing Li
2d To Pseudo-3d Conversion Of "Head And Shoulder" Images Using Feature Based Parametric Disparity Maps, Chaminda Weerasinghe, Philip Ogunbona, Wanqing Li
Professor Philip Ogunbona
This paper presents a method of converting a 2D still photo containing the head & shoulders of a human (e.g. a passport photo) to pseudo-3D, so that the depth can be perceived via stereopsis. This technology has the potential to be included in self-serve photo booths and, also as an added accessory (i.e. software package) for digital still cameras and scanners. The basis of the algorithm is to exploit the ability of the human visual system in combining monoscopic and stereoscopic cues for depth perception. Common facial features are extracted from the 2D photograph, in order to create a parametric …