Indexing and retrieval of compound color objects using co-occurrence histograms of color and wavelet features
Bibliographic record
Abstract
In this paper, we present a system for the retrieval and indexing of images of compound color objects. Compound color objects are objects that consist of a specific set of colors that are spatially arranged in a unique way. Examples of compound color objects include flags, trademarks, logos, and cartoons. In this paper, we apply our proposed technique to logos and trademarks. We introduces a 5-dimensional cooccurrence histogram that captures color and texture information simultaneously. We use the multi-resolution analysis feature with the Coiflet wavelet to capture the texture information in the image. We call this 5-dimensional histogram the color wavelet co-occurrence histogram (CWCH). We show that the CWCH performs better than the edge gradient histogram (EGH) and the color edge co-occurrence histogram (CECH) and the MPEG-7 edge histogram descriptor (EHD).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".