20180608
An Image Analysis System for Tongue Diagnosis in Traditional Chinese Medicine
We introduced a computer-aider tongue examination system, which can reduce the large variation between the diagnosis results of different doctors and quantize the tongue properties automatically in traditional Chinese medicine (TCM) diagnosis. Several key issues and algorithms in this system are discussed, involving some newly proposed image analysis techniques: i) a new tongue color calibration scheme is proposed to overcome the drawbacks of the previous method; ii) a gradient vector flow (GVF) snake based model integrating the chromatic information of the tongue image is used to extract the tongue body; iii) an unsupervised segmentation method of color-texture regions is adopted to quantitatively analyze the distribution of the substance and the coat on the tongue surface. The experimental results show that the presented system has a great deal of potential for the tongue diagnosis.
28794181
JSEG Based Color Separation of Tongue Image in Traditional Chinese Medicine
The process of color separation of tongue image in traditional Chinese medicine (TCM) is decomposed into two steps: region partition and color classification. In the first step, a partition method based on JSEG is proposed to obtain homogenous regions in the tongue. In the second step, a priori template and some standard color patches are designed to assist the classification according to a priori knowledge from the TCM experts, where the nearest neighbour classifier is applied for color classification. The experimental results show that the proposed approach is greatly promising to computerized tongue diagnosis.
32026454
Color-texture image segmentation by integrating directional operators into JSEG method
We presented a new color-texture image segmentation method that combined directional operators and the JSEG (J measure based SEGmentation) algorithm. In particular, two major contributions were set forth in this paper. (1) The two measures defined in JSEG and HSEG (H measure based SEGmentation) were discussed respectively and then we found the over-segmentation problem of JSEG could be attributed partly to the absence of color discontinuity in the J measure. Moreover, we have also proven in essence the H measure is isotropic operators for edge detection in images. (2) A new measure was proposed by integrating directional operators into the J measure, on which our segmentation method was based. The new segmentation method took account of both textural homogeneity and color discontinuity in local regions. Performance improvement due to the proposed modification was demonstrated on a variety of real color images.
39861836
A Novel Method for Eye Features Extraction
Extraction of the eye features, like the pupil center and radius, eye corners and eyelid contours from the frontal face images often provides us useful cues in many important applications, such as face recognition, facial expression recognition and 3D face modeling from 2D images. Assuming the rough eye window is known, the color information, Gabor features are extracted from the eye window and then these two features and their mutual relationship have been incorporated into the design of our algorithm. Firstly, after the pupil center is detected in H channel of HSV color space, the pupil radius is estimated and refined. Secondly, eye corners are localized using eye-corner filter based on Gabor feature space. Finally, eyelid curves are fitted by spline function. The new algorithm has been tested on our SJTU database and some other pictures taken from the web. The experimental results show that our algorithm has high accuracy and is robust under different conditions.
45767095
A Color Image Segmentation Algorithm by Using Region and Edge Information
A novel segmentation algorithm for natural color image is proposed. Fibonacci Lattice-based Sampling is used to get the symbols of image so as to make each pixel’s label containing color information rather than only as a class marker. Next, Region map is formed based on Fibonacci Lattice symbols to depict homogeneous regions. On the other hand, by applying fuzzy homogeneity algorithm on the image, we filter it to acquire Edge map. To strengthen the ability of discrimination, both the weighted maps are combined to form Region-Edge map. Based on above processes, growing-merging method is used to segment the image. Finally, experiments show very promising results.
3357707
A method for document zone content classification
This paper describes an algorithm to classify each given document zone into one of nine classes and provides a protocol for its performance evaluation. The classification scheme uses an optimized binary decision tree and Viterbi algorithm for HMM to find the optimal solution. Our algorithm was trained and tested on a total of 24,177 zones within the 1600 images from UWCDROM III database. Its accuracy rate is 98.45% with a mean false alarm rate of 0.50%.
10128966
Detecting image orientation based on low-level visual content
Accurately and automatically detecting image orientation is of great importance in intelligent image processing. In this paper, we present automatic image orientation detection algorithms based on both the luminance (structural) and chrominance (color) low-level content features. The statistical learning support vector machines (SVMs) are used in our approach as the classifiers. The different sources of the extracted image features, as well as the binary classification nature of SVM, require our system to be able to integrate the outputs from multiple classifiers. Both static combiner (averaging) and trainable combiner (also based on SVMs) are proposed and evaluated in this work. Furthermore, two rejection options (regular and re-enforced ambiguity rejections) are employed to improve orientation detection accuracy by sieving out images with low confidence values during the classification. Large amounts of experiments have been conducted on a database of more than 14,000 images to validate our approaches. Discussions and future directions for this work are also addressed at the end of the paper.
15802971
Subjective preference of spatio-temporal rate in video adaptation using multi-dimensional scalable coding
Video adaptation allows for direct manipulation of existing encoded video streams to meet new resource constraints without having to encode the video from scratch. Multi-dimensional scalable coding, such as motion-compensated subband coding (MCSBC), offers an effective and flexible representation for video adaptation. In order to develop robust criteria for selecting optimal spatio-temporal rates used in adaptation, knowledge about subjective preference of spatio-temporal rates is needed. We study the optimal temporal frame rate over a wide range of bandwidth (50 kbps to 1 Mbps) using subjective quality evaluation with 128 clips and 31 subjects. We analyze the results using statistical testing methods and investigate the dependence of optimal frame rate on user, bandwidth, and video content characteristics. Our findings indicate agreement among most users and the existence of switching bandwidths at which preferred frame rates change. Dependence of the preference on video content types is also revealed.
17258193
Spatiotemporal video segmentation based on graphical models
This paper proposes a probabilistic framework for spatiotemporal segmentation of video sequences. Motion information, boundary information from intensity segmentation, and spatial connectivity of segmentation are unified in the video segmentation process by means of graphical models. A Bayesian network is presented to model interactions among the motion vector field, the intensity segmentation field, and the video segmentation field. The notion of the Markov random field is used to encourage the formation of continuous regions. Given consecutive frames, the conditional joint probability density of the three fields is maximized in an iterative way. To effectively utilize boundary information from the intensity segmentation, distance transformation is employed in local objective functions. Experimental results show that the method is robust and generates spatiotemporally coherent segmentation results. Moreover, the proposed video segmentation approach can be viewed as the compromise of previous motion based approaches and region merging approaches.
5215725
Linear Complexity versus Pseudorandomness: On Beth and Dai's Result
Beth and Dai studied in their Eurocrypt paper [1] the relationship between linear complexity (that is, the length of the shortest Linear Feedback Shift Register that generates the given strings) of strings and the Kolmogorov complexity of strings. Though their results are correct, some of their proofs are incorrect. In this note, we demonstrate with a counterexample the reason why their proofs are incorrect and we prove a stronger result. We conclude our note with some comments on the use of the LIL test (the law of the iterated logarithm) for pseudorandom bits generated by pseudorandom generators.