An automatic and efficient foreground object extraction scheme

This paper presents a method to differentiate the foreground objects from the background of a color image. Firstly a color image of any size is input for processing. The algorithm converts it to a grayscale image. Next we apply canny edge detector to find the boundary of the foreground object. We concentrate to find the maximum distance between each boundary pixel column wise and row wise and we fill the region that is bound by the edges. Thus we are able to extract the grayscale values of pixels that are in the bounded region and convert the grayscale image back to original color image containing only the foreground object

DETEKSI SISI CITRA TOMOGRAFI SINAR – X MENGGUNAKAN OPERATOR LAPLACE

Dari penelitian terdahulu (Supurwoko, 2004) diketahui bahwa citra tomografi dapat diperoleh dengan menyelesaikan masalah invers. Namun demikian tampang lintang obyek yang dihasilkan mengalami pengaburan pada sisi citranya, terutama jika menggunakan berkas sinar – X sejajar. Oleh karena itu perlu dilakukan pengolahan citra agar citra yang dihasilkan semakin baik dan pengaburan yang menyebabkan kesalahan analisis dapat dihilangkan. Pada penelitian ini pengolahan citra yang digunakan adalah deteksi sisi dengan gradien arah. Sedangkan byek ujinya mempunyai tampang lintang berbentuk“+” dan “H” dengan jumlah proyeksi 4 untuk berkas X sejajar. Data proyeksi dilakukan secara simulasi dengan memanfaatkan sifat linieritas interaksi antara bahan dengan sunar X. Semua proses data dan pengolahannya dilakukan dengan menggunakan bahasa pemrograman C dengan kompiler Borland C ++ versi 5. Dari citra hasil yang diperoleh dapat disimpulkan bahwa deteksi sisi dengan gradien arah dapat digunakan untuk mendeteksi sisi – sisi citra tomografi dengan baik meskipun belum sempurna. Dengan demikian, deteksi sisi dengan operator laplace ini merupakan proses pengolahan citra yang sebaiknya digunakan untuk menganalisa citra tomografi. Kata kunci : berkas sejajar, citra rekonstruksi, deteksi sisi, operator laplace

Hybrid imaging and neural networks techniques for processing solar images

YesSolar imaging is currently an active area of research. A fast hybrid system for the automated detection of filaments in solar images is presented in this paper. The system includes three major stages. The central solar region is detected in the first stage using integral projections. Intensity filtering and image enhancement techniques are implemented in the second stage to enhance the quality of detection in the central region. Local detection windows are implemented in the third stage to detect the positions of filaments and to define various sized arrays to contain them. The extracted arrays are fed later to a neural network for verification purposes

DETEKSI SISI CITRA TOMOGRAFI SINAR – X MENGGUNAKAN OPERATOR LAPLACE

ABSTRAK Dari penelitian terdahulu (Supurwoko, 2004) diketahui bahwa citra tomografi dapat diperoleh dengan menyelesaikan masalah invers. Namun demikian tampang lintang obyek yang dihasilkan mengalami pengaburan pada sisi citranya, terutama jika menggunakan berkas sinar – X sejajar. Oleh karena itu perlu dilakukan pengolahan citra agar citra yang dihasilkan semakin baik dan pengaburan yang menyebabkan kesalahan analisis dapat dihilangkan.Pada penelitian ini pengolahan citra yang digunakan adalah deteksi sisi dengan gradien arah. Sedangkan byek ujinya mempunyai tampang lintang berbentuk“+” dan “H” dengan jumlah proyeksi 4 untuk berkas X sejajar. Data proyeksi dilakukan secara simulasi dengan memanfaatkan sifat linieritas interaksi antara bahan dengan sunar X. Semua proses data dan pengolahannya dilakukan dengan menggunakan bahasa pemrograman C dengan kompiler Borland C++ versi 5.Dari citra hasil yang diperoleh dapat disimpulkan bahwa deteksi sisi dengan gradien arah dapat digunakan untuk mendeteksi sisi – sisi citra tomografi dengan baik meskipun belum sempurna. Dengan demikian, deteksi sisi dengan operator laplace ini merupakan proses pengolahan citra yang sebaiknya digunakan untuk menganalisa citra tomografi. Kata  kunci :    berkas sejajar, citra rekonstruksi, deteksi sisi, operator laplace

A Fast and Accurate Iris Localization Technique for Healthcare Security System

yesIn the health care systems, a high security level is required to protect extremely sensitive patient records. The goal is to provide a secure access to the right records at the right time with high patient privacy. As the most accurate biometric system, the iris recognition can play a significant role in healthcare applications for accurate patient identification. In this paper, the corner stone towards building a fast and robust iris recognition system for healthcare applications is addressed, which is known as iris localization. Iris localization is an essential step for efficient iris recognition systems. The presence of extraneous features such as eyelashes, eyelids, pupil and reflection spots make the correct iris localization challenging. In this paper, an efficient and automatic method is presented for the inner and outer iris boundary localization. The inner pupil boundary is detected after eliminating specular reflections using a combination of thresholding and morphological operations. Then, the outer iris boundary is detected using the modified Circular Hough transform. An efficient preprocessing procedure is proposed to enhance the iris boundary by applying 2D Gaussian filter and Histogram equalization processes. In addition, the pupil’s parameters (e.g. radius and center coordinates) are employed to reduce the search time of the Hough transform by discarding the unnecessary edge points within the iris region. Finally, a robust and fast eyelids detection algorithm is developed which employs an anisotropic diffusion filter with Radon transform to fit the upper and lower eyelids boundaries. The performance of the proposed method is tested on two databases: CASIA Version 1.0 and SDUMLA-HMT iris database. The Experimental results demonstrate the efficiency of the proposed method. Moreover, a comparative study with other established methods is also carried out

Detection of Closed Regions in Digital Images

Abstract- The aim of this work is to introduce a pre-processing step that can be used to detect objects in computer vision systems. The new technique detects the closed shape objects in the input image and neglects all the irrelevant data regions. The detection process starts by implementing the hit-miss transform to produce a binary noise-free image. Watershed transform followed by a novel detection algorithm is applied next to locate and detect the closed shape objects. The Detection algorithm can handle real-life images in real-time mode; it works well even under noise conditions. Keywords: Hit-Miss transform; Watershed transform; Mosaic images; Detection of objects 1