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Plants are to be considered as one of the important things that plays a very essential role for all living beings exists on earth. But due to some unawareness and environment deterioration, some very rare plants are on the verge of extinction. Knowledge of rare leaves used for medicine and other plants is very critical in future. Leaf identification and classification plays a vital role for plant...
Content Based Image Retrieval (CBIR) is a developing trend in Digital Image Processing for searching and retrieving the query image from wide range of databases. Conventional content-based image retrieval (CBIR) schemes have following limitations: 1. It is slow 2. difficult to label negative examples; 3. Accuracy is poor in a single step; 4. users may introduce some noisy examples into the query....
Immense analysis has been done on optical character recognition (OCR). Numerous works has stated for English, Chinese, Devanagari, Malayalam, Arabic scripts, etc. Segmentation has imp phase in OCR and various articles have been published on different segmentation methods like Thinning, histogram etc for different script during last few years. Generally there is not work done on Overlapped and touching...
Transformers are known as one of the most important equipment in power system transmission and distribution network. Safety of transformer insulation is determined mainly by its insulating oil dielectric strength. A major concern which threaten the withstand strength of a liquid insulation is the presence of particle contamination. One of the best methods to detect any abnormality and insulation weakness...
After extracting the candidate region from an image, it is necessary to take a kind of technology to determine whether the split target is a pedestrian. By analysis and feature extraction to segmentations of pedestrian candidate region, the classification of pedestrians has been studied. The pedestrian classifier of the SVM (Support Vector Machines) has been trained with pedestrian's typical characteristics...
Accurate monitoring of urban areas using remote sensing data requires reliable change detection techniques. Nevertheless, while most of the changes are optically visible and easily detectable by an expert user, automatic processes are quite difficult to develop. That is why, the interpretation of changes has remained up-to-now visual in most operational applications in remote sensing. This paper provides...
Scene classification from images is a challenging problem in computer vision due to its significant variability of scale, illumination, and view. Recently, Latent Dirichlet Allocation (LDA) model has grown popular in computer vision field, especially in scene labeling and classification. However, the effectiveness of the LDA model for the scene classification has not yet been addressed thoroughly...
Shape descriptors have been used frequently as features to characterize an image for classification and image retrieval tasks. The problem of recognizing classes of objects in images is important for annotation and indexing of Satellite image databases. In this paper, a comparison between shape and texture features for classification is presented. The classification is based on Support Vector Machine...
Proliferative diabetic retinopathyis a rare condition likely to lead to severe visual impairment. It is characterized by the development of abnormal new retinal vessels. We describe a method for automatically detecting new vessels on the optic disc using retinal photography. Vessel-like candidate segments are first detected using a method based on watershed lines and ridge strength measurement. Fifteen...
Detecting objects in images is very important for several application domains in computer vision. This paper presents an experimental study on data transformation of the feature vector in object detection. We use the modified Pyramid of Histograms of Orientation Gradients descriptor and the SVM classifier to form an object detection model. We apply a simple transformation to the histogram features...
A new and efficient method for casts recognition in urinary sediment microscopic images is proposed in this paper. It combines the shape and texture characteristics of casts, and accordingly, consists of two steps. In the first step, the casts' tube-like shape feature is expressed by a modified method stems from the traditional one which is based on the minimum bounding rectangle(MBR). Instead of...
This paper presents a home-care system for recognizing six kinds of daily activities (including walk, jogging, in-place actions like standing, sitting and squat, stand-to-sit, stand-to-squat, and fall) from videos by a multi-SVM classifier with decision tree structure. The system first detects human blobs by a non-parameter background subtraction method, then extracts shape and motion features from...
One of the main challenges in Intelligent Vehicle is recognition of road obstacles. Our goal is to design a real-time, precise and robust pedestrian recognition system. We choose to use Speeded Up Robust Features (SURF) and a Support Vector Machine (SVM) classifier in order to perform the recognition task. Our main contribution is a method for fast computation of discriminative features for pedestrian...
In 2000, the Cohn-Kanade (CK) database was released for the purpose of promoting research into automatically detecting individual facial expressions. Since then, the CK database has become one of the most widely used test-beds for algorithm development and evaluation. During this period, three limitations have become apparent: 1) While AU codes are well validated, emotion labels are not, as they refer...
Maximally Stable Extremal Region (MSER) has been proved to be a powerful local invariant feature. The original MSER detector only utilizes the intensity space. To get more information from a color image, it is naturally to extract MSERs from H, S and I spaces, or other color spaces. However, the increased MSER set inevitably bring in some unstable MSERs, and this will contaminate the over-all reliability...
Content based retrieval and recognition of objects represented in images is a challenging problem making it an active research topic. Shape analysis is one of the main approaches to the problem. In this paper we propose the use of a reduced set of features to describe 2D shapes in images. The design of the proposed technique aims to result in a short and simple to extract shape description. We conducted...
Recognition of human-vehicle interactions is a challenging problem. The occlusion by vehicles and motion of humans contribute to the difficulty. In this paper, we present a novel approach for the view independent recognition of human-vehicle interactions. The shape based matching of synthetic 3D vehicle models is used for accurate localization of vehicles and for the specification of regions-of-interest...
The way that Alzheimer's disease (AD) invades brain is to destroy its fundamental elements, i.e. neurons. The phenomenon of neuron destruction reflects volume changes on brain tissues such as gray matter, white matter and cerebro-spinal fluid. In the AD-related research, the volumetric analysis of hippocampus is the most extensive study. However, the segmentation and identification of the hippocampus...
Recently a new method for recognition of isolated handwritten Persian digits, based on support vector machines (SVMs), has been introduced. In this research, this method was implemented for the same task with three new modifications, i.e. only one popular shape was considered for digits written in different shapes; sizes of glyphs normalized to digit boundaries; MLP (multi-layer perceptron), SVM/MLP...
Computer vision techniques have been widely used in various applications. In recent years, as energy efficiency have gradually become a important issues, computer vision techniques can be integrated into a smart control system that helps increase the energy efficiency by controlling the turn on of the light based on human detection. However, implement such system that detect walking human in a semi-dark...
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