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Colon cancer causes the deaths of about half a million people every year. The common method of its detection is histopathological tissue analysis, it leads to tiredness and workload to the pathologist. A novel method is proposed that combines both structural and statistical pattern recognition used for the detection of colon cancer. This paper presents a comparison among the different classifiers...
In this paper, we address the problem of interactive image segmentation which segments an image based on user-supplied scribbles. For this purpose, we propose a novel framework that provides consistent performance robust to the location of input seeds. Most of the existing methods, especially random walk-based approaches, strongly depend on initial seed positions, which differ from one user to another...
In this paper, a method of rice integrity detection based on digital image processing technology is proposed. Firstly, the original image is preprocessed with the method of binarization and deburring. Then the adhesion rice is segmented with the segmentation algorithm based on concavity points detection. Finally, contour extraction and optimal threshold are adopted and the rice integrity detection...
This paper deals with extracting lines in handwritten Persian texts. In the presented method, at first, oblique lines and dots pertaining to words that are the main causes of two lines sticking to each other are eliminated. Then, using morphological operations, the remaining components of lines stick to one another. Finally, each line's border is determined using contours. This method was tested on...
A novel application of the Hough transform (HT) neighborhood approach to collinear segment detection was proposed in [1]. It, however, suffered from one major weakness in that it could not provide an effective solution to the case of segment intersection. This paper analyzes a vital prerequisite step, disturbance elimination in the Hough space, and shows why, this method alone, is incapable of distinguishing...
Handwriting stroke reflects how the author faced his world and the emotional honesty. By examining all elements of handwriting and interpreting them separately or integrated, we could generate a sketch of the writer's character traits, emotional disposition and social style using standard of graphology. As image, the analysis of graphology is divided into two approaches that graphics features and...
Binarization of text in natural scene images is a challenging task due to the variations in color, size, and font of the text and the results are often affected by complex backgrounds, different lighting conditions, shadows and reflections. A robust solution to this problem can significantly enhance the accuracy of scene text recognition algorithms leading to a variety of applications such as scene...
Digital document categorization based on logo spotting and recognition has raised a great interest in the research community because logos in documents are sources of information for categorizing documents with low costs. In this paper, we present an approach to improve the result of our method for logo spotting and recognition based on key point matching and presented in our previous paper [7]. First,...
Scale-invariant Feature Transform (SIFT) is an algorithm to find local features in images. SIFT uses Difference-of-Gaussian (DoG) to locate candidate keypoints and performs a detailed fit to locate keypoints, then orientations are added to keypoints and keypoint descriptor is generated for each keypoint. Iris recognition is one of the most reliable biometric authentications. In this paper, we propose...
Antinuclear autoantibodies (ANAs) are important markers to diagnose autoimmune diseases, very serious and also invalidating illnesses. The benchmark procedure for ANAs diagnosis is the indirect immunofluorescence (IIF) assay performed on the HEp-2 substrate. Medical doctors first determine the fluorescence intensity exhibited by HEp-2 cells, and then report the staining pattern for positive wells...
We segment atherosclerotic plaque components in in-vivo MRI and CT data using supervised voxelwise classification. The most reliable ground truth can be obtained from histology sections, however, it is not straightforward to use this for classifier training as the registration with in-vivo data often shows misalignments. Therefore, for training we incorporate uncertainty in the ground truth via ”soft”...
An automated histology analysis is proposed for classification of local image patches of colon histopathology images into four principle classes: normal, cancer, adenomatous and inflamed classes. Shape features based on stroma, lumen and imperfectly segmented nuclei are combined with texture features for classification. The classification is analyzed under the three scenarios: normal vs. abnormal,...
Breast cancer grading of histological tissue samples by visual inspection is the standard clinical practice for the diagnosis and prognosis of cancer development. An important parameter for tumor prognosis is the number of mitotic cells present in histologically stained breast cancer tissue sections. We propose a hierarchical learning workflow for automated mitosis detection in breast cancer. From...
In this paper, we address the problem of representing objects using contours for the purpose of recognition. We propose a novel segmentation method for integrating a new contour matching energy into level set based segmentation schemes. The contour matching energy is represented by major components of Elliptic Fourier shape descriptors and serves as a shape prior to guide the curve evolution. The...
Classifying images of HEp-2 cells from indirect im-munofluorescence has important clinical applications. We have developed an automatic method based on random forests that classifies an HEp-2 cell image into one of six classes. The method is applied to the data set of the ICPR 2012 contest. The previously obtained best accuracy is 79.3% for this data set, whereas we obtain an accuracy of 97.4%. The...
Font can be used as a notion of similarity amongst multiple documents written in same script. We could automatically retrieve document images with specific font from a huge digital document repository. So Optical Font Recognition could be a useful pre-processing step in an automated questioned document analysis system for sorting documents with similar fonts. We propose a scheme to identify 10 different...
For the problem of low resolution, camera movement and target's detail fuzzy in aerial video when detecting and recognizing pedestrian, this paper proposes weighted region matching algorithm based on saliency detection and Kalman filter(KS-WRM). In the preprocessing stage, the KS-WRM algorithm uses saliency detection algorithm, which adds human subjective consciousness to segment pedestrians. The...
A graph matching approach is proposed to retrieve envelope images from a large image database. First, the graph representation of an envelop image is generated based on the image segmentation results, in which each node corresponds to one segmented region. The attributes of nodes and edges in the graph are described by characteristics of the envelope image. Second, a minimum weighted bipartite graph...
The discretization of a HT space results in the ρ value detection error of a line. This paper addresses the ρ-direction precision improvement by compensating for this error. The mage are vertically or horizontally shifted, and a series peak positions are obtained by applying the standard HT (SHT) on these shifted images. The change of ρ value of a line due to these shifts is studied. On one hand this...
Statistical Pattern Recognition is one of the basic techniques for land use/land cover classification of remote sensing image. Focusing on establishing a method to integrate statistical pattern recognition with geosciences' analysis, this paper proposed a segmentation-based remotely sensed imagery classification method, called ISODATA-Geosciences Imagery Classification (ISOGIC). The result from case...
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