Image pattern classification is considered a significant step for image and video processing.Although various image pattern algorithms have been proposed so far that achieved adequate classification,achieving higher accuracy while reducing the computation time remains challenging to date. A robust imagepattern classification method is essential to obtain the desired accuracy. This method can be accuratelyclassify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism.Moreover, to date, most of the existing studies are focused on evaluating their methods based on specificorthogonal moments, which limits the understanding of their potential application to various DiscreteOrthogonal Moments (DOMs). Therefore, finding a fast PET classification method that accurately clas-sify image pattern is crucial. To this end, this paper proposes a new scheme for accurate and fast imagepattern classification using an efficient DOM. To reduce the computational complexity of feature extraction,an election mechanism is proposed to reduce the number of processed block patterns. In addition, supportvector machine is used to classify the extracted features for different block patterns. The proposed scheme isevaluated by comparing the accuracy of the proposed method with the accuracy achieved by state-of-the-artmethods. In addition, we compare the performance of the proposed method based on different DOMs toget the robust one. The results show that the proposed method achieves the highest classification accuracycompared with the existing methods in all the scenarios considered
The texture analysis of cancer cells leads to a procedure to distinguish spatial differences within an image and extract essential information. This study used two test tumours images to determine cancer type, location, and geometric characteristics (area, size, dimensions, radius, etc.). The suggested algorithm was designed to detect and distinguish breast cancer using the segmentation-based threshold technique. The method of texture analysis Grey Level Size Zone method was used to extract 11 features: Small Zone Emphasis, Large Zone Emphasis, Low Grey Level Zone Emphasis, High Grey Level Zone Emphasis, Small Zone Low Grey Level Emphasis, Small Zone High Grey Level Emphasis, Large Zone Low Grey Level Emphasis, Large Zone High Gre
... Show MoreMany approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good
In the present paper, Arabic Character Recognition Edge detection method based on contour and connected components is proposed. First stage contour extraction feature is introduced to tackle the Arabic characters edge detection problem, where the aim is to extract the edge information presented in the Arabic characters, since it is crucial to understand the character content. The second stage connected components appling for the same characters to find edge detection. The proposed approach exploits a number of connected components, which move on the character by character intensity values, to establish matrix, which represents the edge information at each pixel location .
... Show MoreForeground object detection is one of the major important tasks in the field of computer vision which attempt to discover important objects in still image or image sequences or locate related targets from the scene. Foreground objects detection is very important for several approaches like object recognition, surveillance, image annotation, and image retrieval, etc. In this work, a proposed method has been presented for detection and separation foreground object from image or video in both of moving and stable targets. Comparisons with general foreground detectors such as background subtraction techniques our approach are able to detect important target for case the target is moving or not and can separate foreground object with high det
... Show MoreIn recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection
... Show MoreIn recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the
... Show MoreSome degree of noise is always present in any electronic device that
transmits or receives a signal . For televisions, this signal i has been to s the
broadcast data transmitted over cable-or received at the antenna; for digital
cameras, the signal is the light which hits the camera sensor. At any case, noise
is unavoidable. In this paper, an electronic noise has been generate on
TV-satellite images by using variable resistors connected to the transmitting cable
. The contrast of edges has been determined. This method has been applied by
capturing images from TV-satellite images (Al-arabiya channel) channel with
different resistors. The results show that when increasing resistance always
produced higher noise f