The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Graph-cut optimization has been successfully applied in many image segmentation tasks. Within this framework color information has been extensively used as a perceptual property of objects to segment the foreground object from background. There are different representations of color in digital images, each with special characteristics. Previous work on segmentation lacks a systematic study of which...
The paper designs and implements a real-time speed limit sign recognition and over-speed warning system on android mobile devices. The proposed system can inform car drivers the current speed limit by recognizing speed limit signs. Furthermore, we also combine GPS function with speed limit sign recognition to warn car drivers in over-speed condition which can avoid car drivers to get punished tickets...
In an aging society, a service robot will come into our life. It is important for a robot to identify an object specified by human speech from several objects. Human may request an object for the robot by its name, and/or color name etc. Although there are some research about the method for the object identification based on its name, the object identification based on its color is not discussed enough...
The authors propose a novel pre-processing phase that can be integrated into conventional methods to detect and recognize planar visual objects in printed materials with low computational cost and higher accuracy. A simple yet efficient visual saliency estimation technique based on regional contrast is developed to quickly filter out low informative regions in printed materials. By eliminating noisy...
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...
For the need of actually combining RGB data and depth input in computer vision research, new RGB-D features for object recognition are proposed. We present six kinds of RGB-D kernel matching functions on kernel view. They have the capability of capturing different RGB-depth cues including position, size, shape and distance. Due to the infinite dimensional character in Gaussian space, it is computationally...
In this paper, an approach for object recognition based on wavelet transform is presented. This approach decomposes the input image into sub-bands by using the multiresolutional analysis, Discrete Wavelet Transform (DWT). As each sub-band in the decomposed image contains useful information about the object, the mean of each sub-band is considered as features. This approach is tested on Columbia Object...
Use of digital image analysis for the identification of seeds has not been recognized as a validated method. Image analysis for seed identification has been previously studied, and good recognition rates have been achieved. However, the data sets used in these experiments either contain very few groups of non-verified specimens or little representation of intra-species variations. This study considered...
We describe how a task in computer vision can be effectively resolved by employing Genetic Algorithm. This paper focuses on the problem of semantic segmentation of digital images. We propose to use an improved genetic algorithm for the learning parameters of weak classifiers in a boosting learning set up. We propose a new encoding and genetic operators in accordance with this problem. Beside that,...
In this paper, we propose an approach for object recognition using binary local invariant features and color information. In our approach, we use a fast detector for key point detection and binary local features descriptor for key point description. For local feature matching, the Fast library for Approximated Nearest Neighbors (FLANN) is applied to match the query image and reference image in data...
To recognize objects within narrow categories, it is important to extract effective features from small number of training samples. In this paper, first we discuss several depth features to improve object recognition accuracy. After that, we also discuss feature dimension reduction when we have insufficient training samples.
In this paper we propose a method to detect salient object in still image and non-slow motion background video. The key technique is measuring pixel blurriness. Generally speaking, salient object was taken in focus, pixels within salient object should be sharper than those within background. In the first step image intensity is extracted, and then four different-size average filters are applied to...
This paper presents a novel hybrid method for tea color separation using image processing and artificial intelligence techniques. The objective of this research is to identify the stalk particles which reduce the quality of tea, without removing good particles with the intention of increasing the income of the tea manufacturing process. In order to achieve this goal it is important to identify the...
This paper presents a novel method for recognizing the channel logos from the streamed videos in real time, which has various applications for value added services in the connected TV space. The results presented are based on the accuracy and performance in terms of time complexity of the channel logo recognition algorithm. The prototype is developed in X86 platform and then ported on a commercially...
This paper presents a simplified image recognition algorithm. This algorithm, with a combination of region-based matching and feature-based matching, uses only a small amount of computation to achieve rapid identification of a target positioning. Experiments indicate that the algorithm shows smooth and fast recognition and accurate positioning on a single video track of the dynamic object recognition.
There are many computer vision algorithms developed for visual (scene and object) recognition. Some systems focus on involved learning algorithms, some leverage millions of training images, and some systems focus on modeling relevant information (features) with the goal of effective recognition. However, none of these systems come close to human capabilities. If we study human responses on similar...
Dependable 3D perception modules are essential for safe operation of robotic platforms. Furthermore, robot navigation and localization as well as object recognition tasks also require processing 2D color camera images. This information could be synchronously delivered by stereo vision sensors with the 3D information automatically mapped onto the 2D camera image. However, embedded real-time stereo...
The research of autonomous robots is one of the most important issues in recent years. In the numerous robot researches, the humanoid robot soccer competition is very popular. The robot soccer players rely on their vision systems very heavily when they are in the unpredictable and dynamic environments. This paper proposes a simple and fast real-time object recognition system for the RoboCup soccer...
When designing intelligence for a car many different tasks can be performed. Some of these tasks cannot easily be performed by conventional algorithms in comparison with the human brain. Recently, such intelligence has often been reached by using probability based systems. In this paper, Hierarchical Temporal Memory (HTM) is used to implement one of these tasks, namely traffic sign recognition. In...
The recent introduction of smartphones has resulted in an explosion of innovative mobile applications. The computational requirements of many of these applications, however, can not be met by the smartphone itself. The compute power of the smartphone can be enhanced by distributing the application over other compute resources. Existing solutions comprise of a light weight client running on the smartphone...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.