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This paper aims to develop an effective flower classification approach using the technology of feature extraction. With this regard, a fused descriptor based on Pyramid Histogram of Visual Words (PHOW) is used to extract the color, texture and contour information of flower image. Secondly, Dictionary Learning and Locality-constrained Linear Coding (LLC) are operated on PHOW feature and then images...
Action recognition has been a growing research topic in computer vision due to its great potentials for real-world applications. In this paper, we develop an effective action recognition approach based on salient object detection and propose a new feature descriptor to represent the changes of edge orientation. Firstly, we detect salient objects from each frame of a video sequence and generate edge...
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...
This paper describes an efficient method for drowsiness detection by three well defined phases. These three phases are facial features detection using Viola Jones, the eye tracking and yawning detection. Once the face is detected, the system is made illumination invariant by segmenting the skin part alone and considering only the chromatic components to reject most of the non face image backgrounds...
In order to solve the detection problem of bad real-time performance and robustness in complex scene, a new method for soft cascade classifier based on SVM was built. The image features can be extracted by the algorithm of using ORBP feature descriptor. Then, based on efficiently combining manifold features and cascaded threshold, a multistage classifier frame is introduced in detail. To ensure the...
In the paper, we present a method for evaluating the quality of tongue images in Traditional Chinese Medicine (TCM). First, we preprocess the original images to segment the tongue images. Second, geometric features, texture features and spectral entropy features and spatial entropy features based on Spatial-Spectral Entropy-based Quality (SSEQ) index of tongue images are extracted respectively to...
Image retrieval is an active research area for the last two decades. This area is gaining more importance as the multimedia content over the internet is increasing. Color Texture and shape are the low level image descriptor in Content Based Image Retrieval. These low level image descriptors are used for image representation and retrieval in CBIR. This paper presents a Content Base Image Retrieval...
Handwritten digit recognition is a subproblem of the well-known optical recognition topic. In this work, we propose a new feature extraction method for offline handwritten digit recognition. The method combines basic image processing techniques such as rotations and edge filtering in order to extract digit characteristics. As classifiers, we use k-NN (k Nearest Neighbor) and Support Vector Machines...
Hoarding is a complex and impairing psychiatric disorder and a public health problem. Traditionally it is assessed through observation and interview, but recently a new method has been proposed where living quarters of an individual are visually compared with a set of template images ranked according to the “Clutter Image Rating” (CIR) scale from 1 to 9. However, such an assessment is time-consuming,...
Today iris recognition systems are extensively used for security and authentication purposes due to their simplicity and high reliability. But these systems face a major challenge of being spoofed by high quality printed iris images or pictures captured by camera. The problem is aggravated by use of varying illumination conditions in an attack access attempt. This paper investigates spoofing attempts...
The paper proposes a mobile application for clothing coordination, which could be of great benefit for stores and people seek for fashion advices. The application matches apparel image input with, previously saved apparel images, and then provides the user with the possible matching suggestions based on the apparel outline and dominating colors. For this purpose two Region of Interest (ROI) extraction...
The automated understanding of textual information from the image is the main goal of Scene Text Recognition (STR). STR is very difficult due to several reasons such as viewing angle and lighting, which are not carefully controlled and very little amount of linguistic context contained in scene images due to which other objects present in the image can interfere the recognition process. Most of the...
From the early days, images are being generally accepted as a proof of occurrence of the past events. The availability of low cost hardware and software tools, makes easy to create and manipulate digital images with no obvious traces. This has led to the situation where one can no longer take the integrity and authenticity of the digital images for granted. In many cases, the images are copied from...
Text detection in image is always a significant part in image semantic understanding, and detection of Uyghur text is a special and extensible application. In this paper, we propose a Uyghur text detection on the basis of the learning of a baseline structure, which generated from texture feature of the text. Firstly, texture features of the image are extracted and texts are classed by a SVM classifier,...
Human detection in images is a fast growing and challenging area of research in computer vision with its main application in video surveillance, robotics, intelligent vehicle, image retrieval, defense, entertainment, behavior analysis, tracking, forensic science, medicalscience and intelligent transportation. This paper presents a robust multi-posture human detection system in images based on local...
With the increasing number of aerial and satellite image sources, automated interpretation algorithms are becoming more and more crucial. Automatically determining the cloud coverage reduces image preprocessing time and aids automatic image exploitation algorithms about where to look. The proposed method makes use of both color and texture characteristics of cloud regions. The image is divided into...
In this paper, we propose a supervised approach to find out the probabilistic mapping of semantic contours in color images. We prepare a new color image modifying the RGB color planes to incorporate reasonable within-object contrasts in all the color planes. Color gradient based features are then extracted from this altered version of color image. Next, multiple support vector machines (SVMs) are...
Manual annotation of images is usually a mandatory task in many applications where no knowledge about the image is available. In presence of huge number of images, this task becomes very tedious and prone to human errors. In this paper, we contribute in automatic annotation of ancient manuscripts by discovering manuscript calligraphy. Ancient manuscripts count a very large number of Persian and Maghrebi...
Breast cancer is one of the leading causes of cancer death for women. Early detection of breast cancer is crucial for reducing mortality rates and improving prognosis of patients. Recently, 3D automated breast ultrasound (ABUS) has gained increasing attentions for reducing subjectivity, operator-dependence, and providing 3D context of the whole breast. In this work, we propose a breast mass detection...
The proper identification of the traffic signs can ensure driving safety and can play a very important role in reducing the number of road accidents significantly. This paper represents a uniform way to detect the speed limit traffic signs and to confirm it by recognizing the sign's speed number. In this system, firstly the red color objects are segmented from an image using LVQ. Secondly, detected...
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