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3D point cloud classification is an important task in applications for many areas such as robotics, urban planning and augmented reality. 3D sensors measure a high amount of points in the 3D scene objects' surface at a high collect rate, so robust techniques are needed to process all input data and also deal with some imprecision. A common solution for these tasks is the use of robust features extraction...
This study describes a method for using a camera to automatically recognize the speed limits on speed-limit signs. This method consists of the following three processes: first (1) a method of detecting the speed-limit signs with a machine learning method utilizing the local binary pattern (LBP) feature quantities as information helpful for identification, then (2) an image processing method using...
In this paper, we propose a patched-based deep Boltzmann shape priors for visual tracking. The shape priors are generated from deep Boltzmann machine network. The network consists of three layers of hidden and visible units. The generated shapes not only maintain general shapes from a variety of poses, but also entail local modifications with high probability.
The idea of lip reading as a visual technique which people may use to translate lip movement into phrases without relying on speech itself is fascinating. There are numerous application areas in which lip reading could provide full assistance. Although there may be a downside to using the lip reading system, whether it may range from problems such as time constraint to minor word recognition mistakes,...
This paper deals with classification algorithms as one of the basic principles of pattern recognition. We analyze their effect to a feature space and compare the type and the shape of the separating and decision surface, respectively. We proposed a novel classification approach based on Cumulative Fuzzy Membership Function that creates a decision surface in a different way as an MF ARTMAP neural network...
Human beings have inseparably attached biofield with physical body. This is now universally accepted. Scientific experiments have conclusively proved that the state of mind, i.e. the thought process, is responsible for generating different characteristics of biophotons. Detection, measurement, and even two dimensional imaging of ultraweak biophotons emission have been reported. With rapid progress...
In most big cities, firearm assault is a common crime. Some state of the art research aim to recognize firearms once they were fired. However, to prevent this type of criminal behavior it is necessary to detect firearms in real time, before they are fired, and maintaining at minimum false alarms. In this paper, we propose a method to detect hand guns by using its shape and real dimensions. The proposed...
Pollen granules are one of the most stable microstructures of herbal flowers, and their ektexines possess strong anti-acid, anti-base and anti-biolysis properties. Therefore, the microstructures of pollen granules are not destroyed during storage, manufacturing and the production of different preparations. The shapes, sizes and colors of pollen granules are different in different families, genera...
Production of high quality wheat has a great importance especially in the solution of nutrition problems. It is necessary to make decomposition for specifying the quality. Here, high quality and unclassified wheat recognition are realized. The most distinctive feature between high quality and poor quality wheat is the shape difference. In this study, Bag of Contour Fragments (BCF) was used as a shape...
Nowadays, image processing is getting more popular due to the daily increase of diverse data acquisition methods such as digital scanners and cameras. Due to the high volume of archived documents, automatic document classification methods can help to save the time and space in digital document organization. Logos in official and business documents are used to identify document identities. Different...
Automated object's activity analysis has been and still remains a challenging problem and motion trajectories provide rich spatiotemporal information for this purpose. This paper presents a novel descriptor to analyze object activity based on object trajectories. In the proposed descriptor extraction technique, object's change in direction is extracted in different level of resolution. One of the...
Machine vision has become popular in new manufacturing industries, where image classification and recognition algorithms are useful for many production processes. However, they have limitations. If the image of the product is unclear, for example because of the shape of the product, it is very difficult to correctly classify or recognize the product. This paper proposes a new technique to improve...
Image classification and recognition algorithms are useful for industrial manufacturing processes; however, the algorithms have limitations. If the products have no special features, images may be unclear. Then, it is difficult to correctly classify or recognize a product using traditional algorithms. Therefore, this paper proposes a technique to enhance a recognition algorithm by using additional...
Recognizing and localizing a recurring pattern is a problem with a variety of applications such as classification and localization of home appliances from their activation signals and estimating the relative alignment between records of a natural repetitive electrocardiography (ECG) signals in Bio-medical data. Most common approaches for recognizing a recurring pattern are generative and focus on...
Leaf recognition is convenient for plant classification and it is an important subfield of pattern recognition. Different leaf features such as color, shape and texture are used as well as different classifiers including artificial neural networks, k-nearest neighbor and support vector machines. In this paper we propose an algorithm based on tuned support vector machine as a classifier and Hu moments...
Deep learning has shown to be very effective in variety of applications including image classification and object recognition. In this paper we use deep autoencoder for compact shape representation learning and image retrieval. In this method the autoencoder is a 4-layer coding network, and the original shape images after scale normalization are used to pre-train the autoencoder in an unsupervised...
In the context of tree species recognition, botanists knowledge was used in different works specially when recognising tree species through leaves. In this paper, two sub-classification strategies for tree species recognition are proposed. For each sub-classification strategy, Basic belief assignment (Bba) was determined and obtained data were fused thanks to a totally adaptive fusion system implemented...
Gait recognition is nowadays an important biometric technique for video surveillance tasks, due to the advantage of using it at distance. However, when the upper body movements are unrelated to the natural dynamic of the gait, caused for example by carrying a bag or wearing a coat, the reported results show low accuracy. With the goal of solving this problem, we apply persistent homology to extract...
As an emerging issue, multi-script signature verification is a recent challenge for current Automatic Signature Verification (ASV) systems. Relevant differences are presented in the morphology and lexicon of the signature images written in different scripts, such as used symbols, shape of the signatures, legibility, etc. These peculiarities could reduce the success of ASV systems, especially those...
Colour, texture, shape, and relative position descriptors are fundamental visual descriptors. In particular, a relative position descriptor is a quantitative representation of the relative position of two spatial objects, and a basis from which models of spatial relationships (like inside, above, around, near) can be derived. The affine properties of visual descriptors have been the subject of much...
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