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Text segmentation is an important problem in document analysis related applications. We address the problem of classifying connected components of a document image as text or non-text. Inspired from previous works in the literature, besides common size and shape related features extracted from the components, we also consider component images, without and with context information, as inputs of the...
The quality of life of people is increasing together with the developing technologies. One of the most important factors affecting daily life is smart cities. The quality of life of people is positively affected by emerging this concept in recent years. Autonomous vehicles confront with the term of the smart city and have become even more popular in recent years. In this study, a system of traffic...
The frequent occurrence of road congestion and traffic accidents has affected people's travel efficiency and travel safety. Traffic sign recognition has become one of the key research objects in intelligent transportation system. This paper studies the identification of road traffic signs based on video images. First of all, collected image will be image preprocessing with image reduction, brightness...
Digital image processing techniques are commonly employed for food classification in an industrial environment. In this paper, we propose the use of supervised learning methods, namely multi-class support vector machines and artificial neural networks to perform classification of different type of almonds. In the process of defining the feature vectors, the proposed method has relied on the principal...
Automated segmentation of cell nuclei is crucial for the early diagnosis of cancer as the characteristics of the cell nuclei are mainly associated with the assessment of malignancy. Only a few research work has been done on automated segmentation of cell nuclei on cytology pleural effusion images, which is poorly handled by previous methods. In addition, cytology pleural effusion image itself is still...
Person re-identification in public areas (such as airports, train stations and shopping malls) has recently received increased attention within computer vision research due, in part, to the demand for enhanced levels of security. Re-identifying subjects within non-overlapped camera networks can be considered as a challenging task. Illumination changes in different scenes, variations in camera resolutions,...
This paper addresses the problem of object-mask registration, which aligns a shape mask to a target object instance. Prior work typically formulate the problem as an object segmentation task with mask prior, which is challenging to solve. In this work, we take a transformation based approach that predicts a 2D non-rigid spatial transform and warps the shape mask onto the target object. In particular,...
Because there are many false targets in the seabed imaging of SAS (synthetic aperture sonar), it is difficult for the automatic alarm of buried column targets. An automatic alarm method for buried targets based on membership classification is proposed in this paper. Firstly, the mean-standard deviation maximum entropy segmentation is used to segment seabed image. Then the area and posture ratio of...
Image over-segmentation, as a pre-processing step of image segmentation, splits the input image into superpixels. Those are small compact regions with irregular shapes. The majority of existing methods for texture feature extraction are not suitable for arbitrarily shaped regions. Therefore, only color information can be used to classify and merge superpixels to create final image segmentation. We...
Detection of repetitive patterns in images is subject of several research papers. The majority of them deals with detection of lattice patterns of repetitive elements. However, there are many situations, when element's repetition doesn't follow any particular pattern. In this paper we focus on the following two objectives. Firstly, our algorithm detects repetitive elements regardless of their relative...
Computer Aided Diagnostic (CAD) tools for differentiating benign and malignant lesions are primarily of great importance. Most of the CAD tools employ a large and complex feature set. In this paper, a CAD system for classifying benign and malignant lesions using optimal feature set is proposed. The optimal feature set included the prominent color, shape and texture features. The feature set used is...
Red blood cell count plays a vital role in identifying the overall health of the patient. Mature Red blood cells undergo morphological changes when blood disorder exists. Automated and Manual techniques exist in the market to count the number of RBCs(Red blood cells). Manual counting involves the use of Hemocytometer to count the blood cells. The conventional method of placing the smear under a microscope...
This paper presents an automated computer vision system of shape defect detection for product quality inspection and monitoring system. Soft drink bottle is used as a tested product for the proposed system. The analysis framework includes data collection, pre-processing, morphological operation, feature extraction, and classification. Morphological operation technique is used to segment the image...
Real-time image processing on low cost embedded systems is still a challenging research area. For this embedded platform, there is a trade-off between accuracy and processing time. We proposed a pedestrian detection method for thermal images that can perform in real-time on a Raspberry Pi embedded system while still keeping the accuracy high. Our detection framework is based on the conventional HOG-based...
Ultrasound image is one of the modalities that is widely used to examine the abnormality of thyroid gland since it is relatively low-cost and safety. Fine needle aspiration biopsy (FNAB) is usually used by radiologists to determine the thyroid nodule whether malignant or benign. Commonly, malignancy of thyroid nodule determined based on shape feature. This research proposes a scheme for classifying...
Detection and segmentation of cells is an important step for classifying the cells as cancerous or non-cancerous. Pathologists use microscopic images for analysis and further diagnosis of cancer. These images contain the microscopic structure of tissues and are stained using some staining components to facilitate the process. Staining process varies due to different stain manufacturers, staining practices...
This paper presents a computer vision-based methodology for human action recognition. First, the shape based pose features are constructed based on area ratios to identify the human silhouette in images. The proposed features are invariance to translation and scaling. Once the human body features are extracted from videos, different human actions are learned individually on the training frames of...
We demonstrate an integrated strategy for identifying buildings in very high resolution satellite imagery of urban areas. Buildings are extracted using structural, contextual, and spectral information. We perform multi-resolution and spectral difference segmentation to obtain a proper object segmentation. First, we use One-Class support vector machine (SVM) in order to determine the man-made structures...
With increasing of the spatial resolution of satellite imaging sensors, object-based image analysis (OBIA) has been gaining prominence in remote sensing applications. However, scale selection in multi-scale segmentation and OBIA remains a challenge, which directly reduces efficiency of land cover mapping. In this study, we presented an object-based land cover mapping using adaptive scale segmentation...
Change detection techniques for remote sensing images are increasingly applied to many fields, such as disaster monitoring, vegetation coverage analysis and so on. How to improve the accuracy of detection has been a critical topic that confuse the researchers for a long time. In this paper, a method combining multiscale segmentation and fusion for high-resolution images is presented. The strategy...
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