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This paper presents an automatic algorithm to recognize the condition of drills on the basis of analysis of the drilling hole images. The algorithm includes the image preprocessing leading to extraction of the diagnostic features, which are used as the input attributes for the classification system. The condition of drill is classified into two groups: the useful one (the sharp enough state) and worn...
Todays, the number of vehicles is rapidly increasing. In parallel, the number of ways and traffic signs have increased. As a result of increased traffic signs, the drivers are expected to learn all the traffic signs and to pay attention to them while driving. A system that can automatically recognize the traffic signs has been need to reduce traffic accidents and to drive more freely. Traffic sign...
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...
Finding a method which allows a computer recognition to be close to human recognition is a goal of many works in the present. We have set this goal too. According to us, we need to find function for simple recognition of shapes in the images as first step of this goal. Result of this method provides input of our system of recognition. System form depends on the result of shape recognition method....
Automatic aircraft recognition is a challenging task. Conventional methods always extract the overall shapes of aircraft at first and then represent the aircraft based on the extracted shape with different features for recognition. The major problem of these methods is that they have a high requirement on shape extraction, which is too idealistic for targets in satellite images. In this letter, we...
To achieve enhanced image recognition, it is necessary to accurately extract the contour of the recognition target from the input image in a preprocessing step. Contour extraction methods based on the active contour model(Snakes) require the operator to specify the parameter values that best catch the shape of the target. However, it is difficult to guess the parameter values since the relationship...
The paper presents different approaches in improving the digital image acquisition with focus on shape recognition. The study is part of a larger project focused on image pre-processing optimization in order to obtain a higher efficiency of automated features recognition. The final target would be to use the results in the field of number plate recognition in road traffic. Structured in two main sections,...
Image-based License Plate Recognition (LPR) algorithms are the core modules of many Intelligent Transportation Systems (ITS). Different algorithms and approaches have been proposed so far. All of these methods have the following three steps in common: License Plate Localization, Character Segmentation & Character Recognition. There are many real-world issues encountered during the design of each...
Target recognition technology is a difficulty in the research field of household service robot. In this paper, connected domains are picked out on the basis of color image segmentation, denoising and graying. The algorithm has improved through shape moment invariants and weighting Euclidean distance. The experiment results show that this algorithm is not sensitive to the light conditions and the perspective...
In this paper, the reflection high-energy electron diffraction (RHEED) pattern during the nano structure formation with the help of image processing is investigated. Nowadays, the growth of self-organised nano structures has been intensively investigated. It is very important to understand their growth process and the knowledge about their shape is particularly significant. The growth of these nano...
One of main tasks in machine vision is able to provide understandable descriptions of objects. A method described here is based on fast Fourier descriptors, which initially incorporated with classic image processing operation can describe shape information in feature space. Fourier descriptor based on chain code and Fourier Transform method is discussed and related invariant property is derived. Experimental...
The scientific significance of automatic logo detection and recognition is more and more growing because of the increasing requirements of intelligent document image analysis and retrieval. In this paper, we introduce a system architecture which is aiming at segmentation-free and layout-independent logo detection and recognition. Along with the unique logo feature design, a novel way to ensure the...
With the development of digital forestry, image processing and pattern recognition technology have been extensively used in the study of forestry research. It is currently a hot research that automatic plant recognition by use of computer. In some developed countries, the technology has been used in the agricultural production. This paper overviews the study of automatic plant recognition by use of...
The G-banding technique is routinely used for generating characteristic banding patterns for chromosome identification and karyotyping. Since G-band patterns are not static, training cytogenetics technologists to master the skills of chromosome analysis is a long process. Furthermore, the opportunities for biology students to access a wide range of different chromosome aberrations for practice are...
The paper deals with the issue of action recognition as an application of the new 3D time-of-flight (ToF) camera, exploiting the special ability of the device to measure distances. Segmentation of moving people is straightforward from the distance information and subsequent steps of the processing chain follow in a classical way. We describe the first results on action recognition using ToF camera...
Many state-of-the-art object recognition systems rely on identifying the location of objects in images, in order to better learn its visual attributes. In this paper, we propose four simple yet powerful hybrid ROI detection methods (combining both local and global features), based on frequently occurring keypoints. We show that our methods demonstrate competitive performance in two different types...
An architecture that is inspired by a human's capability to autonomously navigate an environment based on visual landmark recognition is presented. It consists of pre-attentive and attentive stages that allow visual landmarks to be recognized reliably under both clean and cluttered backgrounds. The pre-attentive stage provides an efficient means for real-time image processing by selectively focusing...
The need for a generic and adaptable object detection and recognition method in images, is becoming a necessity today, given the rapid development of the internet and multimedia databases in general. This paper compares the state-of-the-art in object recognition and proposes a method based on adaptable models for detecting thematic categories of objects. Furthermore, automatically constructed semantics...
A mechanism involving evolutionary genetic programming (GP) and the expectation maximization algorithm (EM) is proposed to generate feature functions automatically, based on the primitive features, for an image pattern recognition system on the diagnosis of the disease OPMD. Prior to the feature function generation, we introduce a novel technique of the primitive texture feature extraction, which...
Object recognition is one of the hot topics in computer vision. Existing techniques for object recognition are based on image processing, which tends to be incapable to recover the topological information of the object. In this paper, based on the analysis of human perceptual habit, a novel strategy for object recognition is proposed. The method perceives an object in the scene by means of existing...
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