Tattoos can provide useful information related to criminal gang activity. Law enforcement can use the information embedded in tattoos to identify and track the criminal history of a suspect. For matching processes, ta...
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ISBN:
(纸本)9781479983407
Tattoos can provide useful information related to criminal gang activity. Law enforcement can use the information embedded in tattoos to identify and track the criminal history of a suspect. For matching processes, tattoo images are difficult to use due to problems such as deformations and weak edge structures. In this paper we describe a tattoo image retrieval and matching system based on a combination of local and global image matching methods to improve matching accuracy. The proposed local shape context combined with SIFT descriptors are used for local features of a tattoo object and global shape is used for overall shape of a tattoo object. The contributions of this paper include the introduction of a multiple different sized-bin polar histograms based local shape context (MHLC) and a global shape descriptor combining the multiple different sized-bin polar histogram and 2D Fourier Transform for robustness of translation, scale, rotation and shape distortions. We also describe robust similarity for local descriptors and a weighted matching method based on local and global descriptors. Our experimental results show that our proposed method performs better than previously published tattoo image retrieval systems.
作者：
Feri CandraSyed Abd. Rahman Abu-BakarComputer Vision
Video and Image Processing Research Lab Electronics and Computer Engineering Department Faculty of Electrical Engineering Universiti Teknologi Malaysia 81310 Johor Bahru Malaysia
Spectral imaging technique such as hyperspectral and multispectral imaging is a combination of imaging and spectroscopy. This powerful technique can provide samples of spectral images, which can be used to analyze a n...
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ISBN:
(纸本)9781479989973
Spectral imaging technique such as hyperspectral and multispectral imaging is a combination of imaging and spectroscopy. This powerful technique can provide samples of spectral images, which can be used to analyze a number of fruit properties. The aim of this study is to develop calibration or predictive model for determining soluble solid content (SSC) of starfruit samples based on their spectral images. Partial least squares (PLSR) and support vector regression (SVR) techniques were applied to build the relationship between the mean spectral data and the reference value. The mean spectral data was extracted from spectral images of each starfruit samples. The simple template for region of interest (ROI) selection and five optimal wavelengths (565.2, 677.2, 736, 873.2 and 943.2 nm) as proposed in previous study were used for extraction of the mean spectral data. The result showed that the calibration model with PLSR and SVR had better performance than the previous study. Moreover, the calibration model with SVR was the best performance for prediction of SSC value of starfruit.
作者：
S DalimanS A R Abu-BakarS H Md Nor AzamComputer Vision
Video and Image Processing (CvviP) Research Lab Department of Electronics and Computer Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia 81310 Skudai Johor MALAYSIA. Sime Darby Research Sdn. Bhd.
Jalan Pulau Carey 42960 Pulau Carey Selangor MALAYSIA.
This paper presents development of Haar-based rectangular windows for recognition of young oil palm tree based on WorldView-2 imagery data. Haar-based rectangular windows or also known as Haar-like rectangular feature...
This paper presents development of Haar-based rectangular windows for recognition of young oil palm tree based on WorldView-2 imagery data. Haar-based rectangular windows or also known as Haar-like rectangular features have been popular in face recognition as used in Viola-Jones object detection framework. Similar to face recognition, the oil palm tree recognition would also need a suitable Haar-based rectangular windows that best suit to the characteristics of oil palm tree. A set of seven Haar-based rectangular windows have been designed to better match specifically the young oil palm tree as the crown size is much smaller compared to the matured ones. Determination of features for oil palm tree is an essential task to ensure a high successful rate of correct oil palm tree detection. Furthermore, features that reflects the identification of oil palm tree indicate distinctiveness between an oil palm tree and other objects in the image such as buildings, roads and drainage. These features will be trained using support vector machine (SVM) to model the oil palm tree for classifying the testing set and subimages of WorldView-2 imagery data. The resulting classification of young oil palm tree with sensitivity of 98.58% and accuracy of 92.73% shows a promising result that it can be used for intention of developing automatic young oil palm tree counting.
Gabor features have been used widely in face identification because of their good results and robustness. However, face identification is strongly affected when the test images are very different from those of the gal...
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Gabor features have been used widely in face identification because of their good results and robustness. However, face identification is strongly affected when the test images are very different from those of the gallery, as is the case in varying face pose. In this paper, a new 2D Gabor-based method is proposed that modifies the grid from which the Gabor features are extracted using a mesh to model face deformations produced by varying pose. Also the Gabor filter kernels are modified by the deformation field computed using the active shape model adjusted to the face. Therefore, the position of the Gabor jets with respect to the face features (eyes, nose, mouth, etc.) is closer to the original position in the frontal face and the modified Gabor filter kernel adjusts to the varying pose. Our method incorporates blocks for illumination compensation by a Local Normalization method, and entropy-weighted Gabor features to emphasize those features that yield proper identification. The method was assessed on the FERET database including pose variations for ±60°, ±40°, ±25°, ±15°, and 0°. We compared our results to those previously published for 2D methods. Our proposed method achieved the highest classification accuracy on the FERET database.
This paper presents a new image abstraction approach, aiming to improve typical image related pattern recognition tasks such as segmentation, tracking, and classification. The proposed image abstraction framework perf...
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This paper presents a new image abstraction approach, aiming to improve typical image related pattern recognition tasks such as segmentation, tracking, and classification. The proposed image abstraction framework performs image denoising and homogeneous region simplification, along with border and region enhancement. The proposed framework consists in a novel generalized approach of common weighted averaging denoising algorithms mixed with Unsharp Masking (USM) border enhancement techniques, to avoid typical USM artifacts as ringing. Results of the different configurations within the image abstraction framework for a cell tracking application are presented.
Accurate modeling of human teeth is mandatory for many reasons. Some of them are (1) Providing comfort to patients during mold process, and (2) Enhancing the accuracy level for oral orthodontist and dental care person...
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This paper presents concepts and some experiment on UAV automatic landing on any flat area without prior knowledge of (detachable) markers' positions. The process consists of two key notions. First, the UAV approx...
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This paper presents concepts and some experiment on UAV automatic landing on any flat area without prior knowledge of (detachable) markers' positions. The process consists of two key notions. First, the UAV approximates 3D positions of four color markers using a single camera stereoscopic scheme. In other words, the aircraft flies and captures images of ground to create depth map of the four markers. Second, it relies on a pose estimation algorithm (here, Homography) to approximate rotational and, especially, translational information between air to ground. What is novel in this concept is z-coordinate of markers on ground can always be normalized based on our kinematic chain. Thus, homography can be used. Additionally, depth estimation using stereo vision with a camera is shown in experimental result. Furthermore, the whole process is also possible without GPS data, which might post problem in some certain situations, e.g. inadequate positioning accuracy for small landing area, or unreliability during warfare.
In this paper, the authors exploit a multispectral image representation to perform more accurate document image binarisation compared to previous color representations. In the first stage, image fusion is employed to ...
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