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Present paper explores gray-level texture features and their extension to color spaces to check their robustness and feasibility in hand detection system. A bare hand detection is affected by uneven illumination, skin tone variation, affine distortions, position variation, complex background, etc., which also effects the performance of features as well as learning ability of classifiers. Despite all,...
Similarity rank lists provide a method for learning generalization of classifiers from examples. Here, we apply it to invariant object recognition and demonstrate that it performs better than other approaches on view and illumination invariant recognition. Recognition from a single view reaches 87% success rate. To study its real world capabilities we introduce subsqare rank matching that works on...
An Image Retrieval (IR) system is used for accessing and retrieving the images from large image database. Content means the image features like color, texture and shape of the image. For Color feature, it is scaling and rotation invariant. It encrypts the color data they are a good component to use under changing lighting conditions. Three color moments are figured per channel (e.g. 6 minutes if the...
Diabetic Retinopathy (DR) is the critical and most common eye related disease. Early detection of DR is the best solution to prevent from this disease. This paper proposes an Image Retrieval technique that search and retrieve the query image from retinal Database. A retrieval process will be developed by extracting color histogram feature and then find the feature vector of desired size by setting...
In this paper, a robust and efficient histogram based template matching method for automatic detection of Optic Disc (OD) in retinal images to help ophthalmologists for diagnosis of retinal diseases is presented. Based on camera field of view (FOV) and image resolution, the OD size estimation algorithm for creation of specific size templates is proposed. Color plane histograms of OD region were used...
In this paper, we introduce a new color texture operator for natural texture classification, the Dominant and Minor Sum and Difference Histograms (DM-SDH) descriptor. The proposed approach allows to incorporate both color and texture information in order to enhance the texture discrimination performance. For this purpose, a vectorial representation of the image is used for the descriptor extraction...
Image segmentation is a basic task in image analysis and understanding and feature extraction is important but difficult. In this paper, we propose an effective feature selection method for color image segmentation which selects a group of mixed color features or channels from some different color spaces according to the principle of the least entropy of pixels frequency histogram distribution. Actually,...
SIMPLE (Searching Images with MPEG-7 (& MPEG-7-like) Powered Localized dEscriptors) is a model that proposes the reuse of well-established global descriptors by localizing their description mechanism on image patches located by local features' detectors. Having displayed impressive retrieval results on two different databases, in this paper we extend the family by replacing the originally picked...
Segmentation of optic disk (OD) is a very important step in automatic Diabetic Retinopathy screening. In this paper, we presented a robust and novel template matching algorithm for automatic detection of OD in retinal images. The size of OD area depends on camera field of view and image resolution. Based on these criteria we formulated and presented OD size estimation algorithm and it is used to create...
To facilitate computer analysis of visual art, in the form of paintings, we introduce Pandora (Paintings Dataset for Recognizing the Art movement) database, a collection of digitized paintings labelled with respect to the artistic movement. Noting that the set of databases available as benchmarks for evaluation is highly reduced and most existing ones are limited in variability and number of images,...
This paper presents a study case for color inspection in quality control applications using color descriptors histogram RGB-1D and histogram TSL and supervised machine learning methods such Support Vector Machine (SVM) and Artificial Neural Networks (ANN). For this, we build three annotated databases, and these are made using real application of quality control like color inspection in forages and...
Automated detection of blood vessel structures is becoming a crucial interest for better management of vascular disease. In this paper, we propose an algorithm for vessel segmentation in digital retinal images based on integral channel features and random forests. In the first stage, preprocessing is performed to obtain the candidate pixels of vessels, then a host of simple features are extracted...
In this paper we compare the performances of three automatic methods of identifying hemangioma regions in images: 1) unsupervised segmentation using the Otsu method, 2) Fuzzy C-means clustering (FCM) and 3) an improved region growing algorithm based on FCM (RG-FCM). For each image, the starting point of the algorithms is a rectangular region of interest (ROI) containing the hemangioma. For computing...
The advent of inexpensive RGB-D sensors pioneered by the original Kinect sensor, has paved the way for a lot of innovations in computer and robot vision applications. In this article, we propose a system which uses the new Kinect 2 sensor in a medical application for the purpose of detection and 3D reconstruction of chronic wounds. Wound detection is based on a per block classification of wound tissue...
This paper proposed a new image tampering detection method based on local texture descriptor and extreme learning machine (ELM). The image tampering includes both splicing and copy-move forgery. First, the image was decomposed into three color channels (one luminance and two Chroma), and each channel was divided into non-overlapping blocks. Local textures in the form of local binary pattern (LBP)...
Image tampering detection is important due to many incidences of tampered images misuse. In this paper, we propose a hybrid approach for image tampering detection using range filter and texture descriptor. First we highlights important details of the image using range filtering. The range filter highlights the edges, contours and important details of the objects in an image. Further we apply texture...
Steganalysis when performed blind is a challenging task providing no clues for the steganalyst. Stego media will influence this process if Steganalysis is performed over clean and uncompressed image formats as such formats do not show off embedding distortions easily. If steganalysis needs to identify low volume payloads, it is yet another concern to unearth and highlight the feeble and delicate artifacts...
Identifying different types of damage is very essential in times of natural disasters, where first responders are flooding the internet with often annotated images and texts, and rescue teams are overwhelmed to prioritize often scarce resources. While most of the efforts in such humanitarian situations rely heavily on human labor and input, we propose in this paper a novel hybrid approach to help...
A near-duplicate video clustering algorithm based on multiple complementary video signatures is proposed in this work. We use three kinds of frame descriptors: RGB histogram, color name histogram, and ternary pattern. Then, we convert each kind of frame descriptors for a video into a video signature based on the bag-of-visual-words scheme. Consequently, we have three signatures to represent the video...
The growth of audiovisual content, and in particular video requires the creation of robust tools for detecting illegal copies. This paper presents an effective approach to search and detect illegal copies in large video databases. This automatic detection operates two local descriptors and their paths through the video. This method allows to reduce the temporal redundancy intrinsically linked to the...
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