Forthcoming and Online First Articles

International Journal of Image Mining

International Journal of Image Mining (IJIM)

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International Journal of Image Mining (3 papers in press)

Regular Issues

  • Face recognition-based car ignition system   Order a copy of this article
    by G.N. Sneha, Golla Vara Prasad 
    Abstract: Revolutions in science and industry has changed many walks of life. The changes are witnessed by the transportations too, everyone got the opportunity to have their own vehicle. Though these options provided better comfort, they have too imposed burden, among them one is providing security to owned vehicle. Though conventional system has option of key and lock facility it consumes some limitations, one can breach the security with the duplicate key. In the proposed paper an attempt is made to provide face lock to car ignition system, the concept of face recognition and machine learning are used together to control the engine. Here, we propose facial recognition system by including a face detection system and face tracking system algorithm using Haar cascade classifier.
    Keywords: machine learning; recognition; Haar cascade classifier; ESP32; tkinter.
    DOI: 10.1504/IJIM.2022.10045085
  • Voting algorithm into CBIR: a review   Order a copy of this article
    by Mawloud Mosbah 
    Abstract: Collectiveness is becoming nowadays the trend and the ubiquitous notion available in almost recent introduced informatics smart systems like: collective intelligence tied to bio-inspired solutions and reactive multi-agent systems. In the context of collectiveness and collective decision making, voting algorithm is an important alternative helping to achieve better accuracy and performance. As any other scientific field, CBIR has taken profit of many recently introduced techniques and methods including voting algorithm. In this paper, we talk about voting algorithm into CBIR through quoting its different utilisation with various operations and sub-operations over the different CBIR components such as ranking, re-ranking, feature extraction and representation, feature selection, clustering and classification. Although that the algorithm is the same in its processing mode, the different utilisation contexts lead to different versions especially regarding the considered resources and targets. The paper, presented as a review, allows then collecting and organising the different works adopting voting algorithm, with its different versions, into CBIR field, and discussing the performance and the efficiency of the algorithm in the different considered contexts.
    Keywords: content-based image retrieval; CBIR; CBIR performance enhancement; CBIR pre-processing; CBIR post-processing; voting algorithm.
    DOI: 10.1504/IJIM.2022.10046840
  • A review of recent image processing techniques for liver tumour diagnosis from CT images   Order a copy of this article
    by Farzaneh Nikroorezaei, Somayeh Saraf Esmili 
    Abstract: By early detection of abnormalities using computational systems, doctors can plan an effective treatment program for the patient and increase the chance of survival. Liver cancer has a low survival rate in comparison to some other cancers and early detection significantly increases the chances of survival for people with liver cancer. This review focuses on computer-aided diagnosis (CAD) systems and describes the various image processing techniques, which have been introduced for automatic detection of liver tumours from computed tomography (CT) images. CAD systems using in liver tumour diagnosis include segmentation of liver and classify tumours whether it is cancerous or not. This paper provides a brief description of recent works that have been done in this field to improve the accuracy and speed of detection and discusses the problems and limitations of methods currently available for liver tumour diagnosis. Finally, open challenges and required researches in the field of liver tumour diagnosis are discussed.
    Keywords: classification; liver tumours; computed tomography; CT; medical image processing; segmentation.
    DOI: 10.1504/IJIM.2022.10050792