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This paper proposes two effective color local texture features, i.e., color local Gabor wavelets (CLGWs) and color local binary pattern (CLBP), for face recognition (FR).This method encodes the discriminative features by combining both color and texture information as well as its fusion approach. To make full use of both color and texture information, the opponent color texture features are used....
This paper discusses the offline signature recognition system in which features are extracted using Discrete Wavelet Transform (DWT) and Principal component analysis (PCA) and the artificial neural network (ANN) is used for the recognition of signature. ANN is used to recognize whether a signature is original or fraud. The user provide the scanned image of signature for computer database, modifies...
In this paper, color facial expression recognition based on color local features is investigated, in which each color facial image is decomposed into three color component images. For each color component image, we extract a set of color local features to represent the color component image, where color local features could be either color local binary patterns (LBP) or color scale-invariant feature...
In this paper a new morphological technique suitable for colour image skeleton extraction is presented. Vector morphological operations are defined by means of a new ordering of vectors of the HSV colour space, which is a combination of conditional and partial sub-ordering. Then, these are used to extract skeletons of colour images in terms of erosions and openings. The proposed method was tested...
Image recognition technologies have gained prominence in a variety of fields, such as automotive and surveillance, with dedicated image-recognition ICs being developed recently [1-2]. Image recognition ICs for an advanced driver assistance system (ADAS) have also been proposed [3]. However, future ADAS applications must support greater numbers of real-time recognition processes simultaneously, with...
With increase in age, there are changes in skeletal structure, muscles mass, and body fat. For recognizing faces with age variations, researches have generally focused on the skeletal structure and body mass. We incorporate weight information to improve the performance of face recognition with age variation which utilizes neural network and random decision forest to encode age variation. This age...
Different from the photometric images, depth images resolve the distance ambiguity of the scene, while the properties, such as weak texture, high noise, and low resolution, may limit the representation ability of the well-developed descriptors, which are elaborately designed for the photometric images. In this paper, a novel depth descriptor, geodesic invariant feature (GIF), is presented for representing...
The pervasiveness of mobile cameras has resulted in a dramatic increase in food photos, which are pictures reflecting what people eat. In this paper, we study how taking pictures of what we eat in restaurants can be used for the purpose of automating food journaling. We propose to leverage the context of where the picture was taken, with additional information about the restaurant, available online,...
Text recognition in images is an active research area which attempts to develop a computer application with the ability to automatically read the text from images. Nowadays there is a huge demand of storing the information available on paper documents in to a computer readable form for later use. One simple way to store information from these paper documents in to computer system is to first scan...
The paper presents a pornographic image recognition using fusion of scale invariant descriptor. The pornographic image means the image contains and shows genital elements of human body having large variability due to poses, lighting, and backgrounds variations. The fusion of scale invariant descriptor that is holistic feature is employed to handle those variability problems. This holistic feature...
This research is to propose a fast and highly accurate object recognition method especially for fruit recognition applications to be used in a mobile environment. Conventional techniques are based on one or more of the basic features that characterize an object: color, shape, texture and intensity, causing performance or accuracy limitations in a mobile environment. Thus, this paper presents a combined...
While emphasizing the intensity or saturation component in order to obtain high-quality color images, keeping the hue component unchanged is important; thus, perceptual color models such as HSI and HSV were used. Hue-Saturation-Intensity (HSI) is a public color model, and many color applications are commonly based on this model. However, the transformation from the HSI model to RGB model after the...
The purpose of this study is to classify the use of intelligent Syaritar system, methods for the detection of illegal logging and changes in forest area in the water sed. The research of intelligent hybrid system methods simulate Syaritar to know and analyze the logging on a sample image of the area of protected forest in the Jeneberang basin river by using sample image pair years 2007 to 2009. On...
In order to overcome the existing fruit recognition method only for single feature recognition which leads the problem of lower recognition rate, this paper proposes a recognition method based on multi-feature and multi-decision. Firstly, we preprocess the fruit image which is to be classified, separateing foreground and background, and then we divide the target area. Secondly, in order to take full...
The fire detection methods by using pure flame or pure smoke often lead to the phenomenon of missing alarm. This paper presents a novel fire video recognition method based on both flame and smoke. Firstly, fire regions of interest are detected using Kalman Filter. Then, three major features of flame including flickering, spatio-temporal consistency and texture feature based on Local Binary Pattern...
To overcome the problem of lacking apparent features, e.g. color or shape, in the process of identifying wheat stripe rust from powdery mildew using computer vision algorithms, a novel directional feature based on Improved Rotation Kernel Transformation (IRKT) is proposed. IRKT can calculate the statistics of the direction distribution of infected leaf images in spatial domain. The statistics calculated...
This paper contains short description of cluster analysis algorithm for the mineral rock recognition in the mining industry. In this paper it describes the algorithm for automatic segmentation of color images of rocks, using the methods of cluster analysis. There are results of studies different color spaces for clustering k-means. Some realizations of this algorithm for computing the grading of mineral...
This paper presents a fresh food recognition system that utilizes the feature fusion extracted from food images captured from optical fibers embedded inside a chopping board. We exploit both local and global features including color, SURF and shape for image representation. In addition, we propose cost-based schemes for feature matching and the Borda count method for feature fusion. An experiment...
Considering the lower accuracy of existing traffic sign recognition methods, a new traffic sign recognition method using histogram of oriented gradient - support vector machine (HOG-SVM) and grid search (GS) is proposed. First, the histogram of oriented gradient (HOG) is used to extract the characteristics of traffic sign. Then the grid search technique is applied to optimize the parameters of support...
Traffic sign recognition contributes to the safety of drivers and people around the car. The system analyzes the road ahead images taken by on-vehicle camera, but blurred and distorted images make it difficult to recognize correct traffic sign. In this paper, we propose a method that deforms from ellipses to perfect circles and applies template matching with distorted sign templates.
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