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Object detection and classification are two very important tasks for quality control in industrial process. The first step of a quality algorithm is the detection of the moving object. Afterwards, the detected object is classified according to its size and color related properties. In this study, an interactive image segmentation method is proposed to detect a moving object. The segmentation method...
In uncontrolled environments, the major challenges in face recognition, such as illumination variation, occlusion, facial expressions and poses, greatly affect the performance of Facial Recognition Systems (FRS) especially those based on 2D information. We introduce, in this paper, a novel feature extraction approach named GLBSIF for face recognition in an uncontrolled environment. In our method,...
Uveal melanoma is a type of tumor that can cause loss of vision, loss of organ or even metastasis and loss of life. Radiotherapy is considered to be the least harmful and successful treatment type among various treatment methods. Radiotherapy should be carried out sensitively without movements of the iris. Therefore, the procedure is mostly performed by local anesthesia. Unfortunately, eye anesthesia...
In this study, the similarity between different art movements is investigated. For this purpose, five different art movements are selected and thirty paintings are determined from different painters. By using these paintings, the similarity between paintings inside art movements and from other modern art movements are shown and classified by using mathematical methods. Computational methods are used...
The most common cause of blindness in the world by far is known to be the Glaucoma condition. The increase in the ratio of cup to the disc area and the thinning of retinal layers are the most common symptoms of Glaucoma. Functional and structural features of the eye should be examined in order to distinguish an eye with Glaucoma from a healthy eye. In this study, the texture information in Optical...
Due to the variability of writing styles and to other problems related to the nature of Arabic scripts, the recognition of Arabic handwriting is still awaiting accurate results. Segmentation of Arabic handwritten words into graphemes poses a major challenge in Arabic handwriting recognition and is highly error prone. In this paper, we adopt the holistic approach which handles the whole word image...
Today, In the content of road vehicles, intelligent systems and autonomous vehicles, one of the important problem that should be solved is Road Terrain Classification that improves driving safety and comfort passengers. There are many studies in this area that improved the accuracy of classification. An improved classification method using color feature extraction is proposed in this paper. Color...
Agriculture is the foundation of our country. India is an agrarian nation where the majority of the populaces rely upon agribusiness. Investigation in farming is pointed towards expanding efficiency and profit. There are several automated systems already available which are developed for irrigation control and environmental monitoring in the field. Hence this project aims to monitor the plant growth...
Aim /Objective: To find an optimum image restoration and classification algorithm for identifying the defects in industrial applications. Methodology: A master dataset for industrial applications has been developed for defect identification and the acquired data is further applied to Non-Local Means algorithm for denoising and image restoration and the restored image is further applied with feature...
The proposed method aims to detect brain abnormality using bilateral symmetry property about the interhemispheric fissure (IHF) of human head scans. MRI brain has structural symmetry between the right cerebral hemisphere (RCH) and left cerebral hemisphere (LCH) of brain cerebrum. Any brain abnormalities due to tumors, hemorrhage, etc disturbs the similarity between the two hemispheres. We split the...
Analysis of lace texture images is a challenging problem because the lace is a soft and extensible material and can be easily deformed. This paper investigates a whole system for lace classification. A first step, based on Otsu's segmentation method, allows to remove the background. Then the lace texture is characterized using local binary patterns (LBP). In order to be robust against rotation the...
This paper addresses the problem of automatic target recognition (ATR) using inverse synthetic aperture radar (ISAR) images. In this context, we propose a novel approach for feature extraction to describe precisely an aircraft target from ISAR images. In our approach, a visual attention model is adopted to separate the salient regions from the background. After that, the scale invariant feature transform...
Fusing multiple features within one biometric modality has attracted increasing attention and interest among researchers during recent decades because the concept is useful in addressing a wide range of real world problems. In this paper, we propose a novel fusion approach that combines two feature extraction algorithms: Local Binary Pattern Histogram Fourier Features (LBP-HF) and Gabor filter technique...
The growth of marine renewable energy and marine protected areas in France leads to a growing need for animal population knowledge at sea. Offshore energy generator projects (wind turbines for example) must obey these regulations and show their harmlessness to the environment, particularly to the wildlife and to protected species, which are vulnerable and threatened. This paper presents a supervised...
This paper proposed an automated system for grading of colorectal cancer using image processing method. Almost, half a million people die every year due to colon cancer. Histopathological tissue analysis is a common method for its detection, which needs an expert pathologist. Screening for this cancer is effective for prevention as well as early detection. The method proposed segment the glands automatically...
The most widely used classification techniques for whole brain image classification rely on kernel machines such as support vector machines and Gaussian processes, due to their computational efficiency, accurate prediction and suitability to tackle the combination of small sample sizes and high dimensionality that make neuroimaging data a challenging problem. Such methods generally make use of linear...
Osteoarthritis (OA)is a degenerative joint disease which is most prevalent in the knee joint. It can be characterized by the gradual loss of articular cartilage. The knee OA-affected bones slide together due to degradation of cartilage, causing joint pain, swelling, stiffness and eventual loss of motion. Magnetic resonance imaging (MRI) is the most suitable non-invasive imaging modality to detect...
Ground Penetrating Radar (GPR) senses dielectric discontinuities below the surface. Thus, it can detect low-metal and non-metal landmines. However, it detects not only landmines but also all objects under the ground and therefore, false alarm rates of GPR are very high. Powerful feature based algorithms are necessary to reduce false alarm rates and to distinguish landmine from clutter that causes...
Malwares can create new malware samples which have different size, structure and operation mode but same functionality in each metamorphic code generation via malicious code obfuscation methods. So they can bypass traditional signature-based malware detection systems. In this study, a pattern recognition based system that detects metamorphic malware by using summary structure of Malware Analysis Intermediate...
In this study, gender prediction is investigated for the face images. To extract the features of the images, Local Binary Pattern (LBP) is used with its different parameters. To classify the images male or female, K-Nearest Neighbors (KNN) and Discriminant Analysis (DA) methods are used. Their performances according to the LBP parameters are compared. Also classification methods' parameters are changed...
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