International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 2 (March-April 2026) Submit your research before last 3 days of April to publish your research paper in the issue of March-April.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 8 Issue 2
March-April 2026

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Enhancement of CSIFT Algorithm for Improved Feature Extraction in Psoriasis Image Analysis

Author(s) Ms. Aiyanne Yori Quintos Perdigon, Ms. Julianne Cyrille Tantoco Rico, Prof. Raymund M. Dioses, Dr. Khatalyn E. Mata
Country Philippines
Abstract The precise extraction of lesion features for psoriasis analysis is frequently hindered by the computational latency and "feature blindness" inherent in standard image processing algorithms, which often struggle to capture the subtle texture of organic skin lesions. Addressing the critical trade-off between execution efficiency and diagnostic sensitivity, an Enhanced Color Scale-Invariant Feature Transform (CSIFT) was engineered to optimize the feature extraction architecture for dermatological analysis through three pivotal technical interventions: the replacement of iterative pixel-wise computations with Vectorized Matrix Operations, the implementation of a Texture-Aware Detection module utilizing Adaptive Cr-Otsu Masking with Hybrid Harris Corner detection, and the integration of RootSIFT Normalization. Comparative performance analysis revealed a transformative improvement over the Standard method, as the proposed vectorization strategy achieved an 83.62% reduction in processing overhead, lowering the average execution time from 15,962.29 ms to 2,615.38 ms. Furthermore, the system resolved the loss of low-contrast details, recording a 218% increase in keypoint density from an average of 200.82 to 639.97 points while simultaneously improving the Matching Score to 97.06% compared to the Standard model’s 61.00%. These findings confirm that the Enhanced CSIFT provides a mathematically robust, accurate solution for dermatological imaging, effectively bridging the gap between computational speed and the precision required for clinical assessment.
Keywords Color Scale-Invariant Feature Transform, Feature Extraction, Psoriasis
Field Computer > Data / Information
Published In Volume 8, Issue 1, January-February 2026
Published On 2026-02-28
DOI https://doi.org/10.36948/ijfmr.2026.v08i01.70256
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 8 Isu 2Cover Page Vol 8 Isu 1Cover Page Vol 7 Isu 6

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com
Powered by Sky Research Publication and Journals