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This paper presents a real-time computer visionbased Bengali Sign Language (BdSL) recognition system. The system detects the probable hand from the captured image. The system uses Haar-like feature-based cascaded classifiers to detect the hand in each frame. From the detected hand area, the system extracts the hand sign based on Hue and Saturation value corresponding to human skin color. After normalization...
This paper presents an efficient image exploration scheme for the unshaped object using semantic modelling. The local regions of an image have been classified with respect to the frequency of occurrences. The semantic concept is evaluated using RGB histogram dissimilarity factor, overall dissimilarity factor and regional dissimilarity factor. The dissimilarities determine the local concept with accuracy...
Content based image retrieval has become a major research interest recently. This paper presents an improved image similarity measure for image retrieval system. In the region based image comparison, two images are usually compared in terms of sum of the Euclidean distances among their regions. In this work, the image similarity measure is enhanced through a fuzzyfication of regions' importance and...
In order to avoid the over-segmentation problem caused by original watershed transform and improve the segmentation precision of Mycobacterium Tuberculosis (MTB) images, a novel segmentation algorithm is proposed based on automatic-marker watershed transform. The automatic marker is accomplished by Gaussian weighted adaptive threshold segmentation and local minimum points search within gradient image...
The aim of this paper is to develop an effective classification approach based on Random Forest (RF) algorithm. Three fruits; i.e., apples, Strawberry, and oranges were analysed and several features were extracted based on the fruits' shape, colour characteristics as well as Scale Invariant Feature Transform (SIFT). A preprocessing stages using image processing to prepare the fruit images dataset...
The spike of a cereal plant is the grain-bearing organ whose physical properties are therefore critical components for plant yield. The ability to detect spikes from 2D images of cereals, such as wheat, provides vital information on tiller number and plants yield potential. We propose a novel spike detection method, which uses both RGB and fluorescence images. Firstly, an improved colour index method...
This paper presents the detection and localization methods of entrance and staircase markers for the team E-Mobile in TechX Challenge 2013. Autonomous vehicles are required to detect and locate traffic cones beside the indoor entrance and staircase. One big challenge is from the unpredictable lighting conditions and environment. Different practical techniques such as color space selection, segmentation,...
Images and videos captured by cell phones are very important carriers of information amongst user generated multimedia contents. These carriers can be used in solving many forensic problems such as identification of movie piracy, insurance cases, child pornography, and other applications involving identifying/verifying source cell phones. This paper evaluates the effectiveness of Image Quality Measures...
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...
Visual information obtained from endoscopy in laparoscopic surgery plays an important role in surgery navigation and provides a mean for efficient and effective image-based instrument tracking. Instrument tracking based on monocular vision is a well-researched field, in recent years, stereo vision based techniques have attracted the interests of the academic community. In this work, we propose two...
Given a spatial raster framework F, a set of explanatory feature maps, training and test samples with class labels on F, as well as a base classifier type, the problem of ensemble learning in raster classification aims to learn a collection of base classifiers to minimize classification errors. The problem has important societal applications such as land cover classification but is challenging due...
Almost every computer vision applications used background subtraction method to detect moving objects from video sequence. Moving object detection and tracking is generally the first step in many applications such as face detection, traffic surveillance, object recognition, detection of unattended bags, people counting etc. Background modeling is very useful and effective method for locating objects...
In order to utilize identification to the best extent, we need robust and fast algorithms and systems to process the data. Having palmprint as a reliable and unique characteristic of every person, we extract and use its features based on its geometry, lines and angles. There are countless ways to define measures for the recognition task. To analyze a new point of view, we extracted textural features...
This paper presents a GPU-based system for real-time traffic sign detection and recognition which can classify 48 different traffic signs included in the library. The proposed design implementation has three stages: pre-processing, feature extraction and classification. For high-speed processing, we propose a window-based histogram of gradient algorithm that is highly optimized for parallel processing...
Millions of people die from Diabetes Mellitus every year. Recently, researchers have discovered that Diabetes Mellitus can be detected in a non-invasive manner through the analysis of human facial blocks. Although algorithms have been developed to detect Diabetes Mellitus using facial block color features, use of its texture features to detect this disease has not been fully investigated. In this...
The objective of this paper is to evaluate Bag-of-Colors (BoC) descriptor for land use classification. BoC can be used either as a global or local descriptor. In this paper we present and evaluate both approaches. We analyze the influence of different parameters on classification accuracy and introduce a modification of descriptor extraction process, which significantly influences the classification...
In this paper, we propose a real-time architecture of multiple features extraction for vehicle verification. First, we set a range of YCbCr values to extract the pixels belonging to vehicle back lights. The density of light is computed by the number of the extracted pixels, and considered as the first feature. The second feature is the location of license plate. It is determined by Searching Area...
A biometric-based techniques emerge as the promising approach for most of the real-time applications including security systems, video surveillances, human-computer interaction and many more. Among all biométrie methods, face recognition offers more benefits as compared to others. Diagnosing human faces and localizing them in images or videos is the priori step of tracking and recognizing. But the...
An improved classification method based on KMeans using HSV color feature is introduced in this paper. It is implemented by extracting three color features (hue, saturation, value) for K-Means clustering. Compared with the traditional K-Means clustering, the experimental results turn out that our proposed method is better than K-Means in classification accuracy and performance.
As a significant feature of vehicle, the color feature plays an important role in the intelligent transportation systems. However, the color feature is easily affected by the variations of the lighting condition. In this paper, we present a new method for vehicle color recognition, which is based on license plate color. The color of license plate is recognized by the prior knowledge and the recognition...
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